This is the most inspiring Quaker writing I know of -
Nobel Peace Prize 1947
Award ceremony speech
Presentation Speech by Gunnar Jahn*, Chairman of the Nobel Committee
The Nobel Committee of the Norwegian Parliament has awarded this year’s Peace Prize to the Quakers, represented by their two great relief organizations, the Friends Service Council in London and the American Friends Service Committee in Philadelphia.
https://www.nobelprize.org/prizes/peace/1947/ceremony-speech/
. . .
"This is the message of good deeds, the message that men can find each other in spite of war, in spite of differences in race. Is it not here that we have the hope of laying foundations for peace among nations, of building it up in man himself so that the settling of disputes by force becomes impossible? All of us know that we have not yet traveled far along this road. And yet – when we witness today the great willingness to help those who have suffered, a generosity unknown before the war and often greatest among those who have least, can we not hope that there is something in the heart of man on which we can build, that we can one day reach our goal if only it be possible to make contact with people in all lands?"
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searched today on ...
We utterly deny all outward wars and strife and
fighting with outward weapons for any end or under any pretense whatever;
this is our testimony to the whole world
George Fox and others, to Charles II
of England, 1660/61 (1)���
Found too -
- The Journal of George Fox: The spiritual autobiography of one of the founders of Quakerism, detailing his experiences and the early days of the movement.
- The Journal of John Woolman: Considered a masterpiece of spiritual autobiography, this journal is known for its deep introspection and powerful witness against slavery and war.
- A Testament of Devotion by Thomas Kelly: A widely read book that explores the inner life and the experience of God's presence, often cited as a key text in Quaker spirituality.
- The Inner Life by Rufus M. Jones: A work by a prolific and influential Quaker thinker, exploring the nature of spiritual experience and the "inner light".
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https://www.nobelprize.org/
What are inspiring #QuakerWritings for you/thee? Glad to have attended #SilentQuakerMeetingOnline this morn https://fmcquaker.org/
Greetings. This is the most inspiring #QuakerWriting I know of: #NobelPeacePrize1947: Award ceremony speech by #GunnarJahn https://t.co/uQo4gBSeIY
— Scott_GK_MacLeod_WUaS_worlduniversityandschool.org (@scottmacleod) September 28, 2025
What are inspiring #QuakerWritings for you/thee? Glad to have attended #SilentQuakerMeetingOnline this morn https://t.co/7Rq65mWgkP~
https://x.com/scottmacleod/
https://x.com/Q_YogaMacFlower/
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Nobel Peace Prize 1947: Award ceremony speech
Presentation Speech by Gunnar Jahn*, Chairman of the Nobel Committee
https://www.nobelprize.org/
What are inspiring Quaker writings for you / thee?
Scott ~Friendly-inspired: sgkmacleod@
Scott GK MacLeod ~ https://x.com/Q_YogaMacFlower
https://fmcquaker.org/
most inspiring Quaker writing that I know of: The Nobel peace prize address 1947 by Gunnar Jahn
https://www.nobelprize.org/
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(#HaikuIsh & #MITOCWcentric)
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Civil rights and Black Power
- Context: Founded by Huey P. Newton and Bobby Seale in Oakland, California, the Black Panther Party was a revolutionary organization that sought to protect African American communities from police brutality. The Ten-Point Program articulated its demands for economic, social, and political justice.
- Key Demands:
- "What We Want": The list of demands included freedom, full employment, decent housing, and education that teaches "our true history".
- "What We Believe": This section provided the philosophical justification for the demands, arguing for the right of Black people to self-determination and self-defense against a racist government.
- Legacy: The Ten-Point Program became one of the most influential documents of the Black nationalist movement and inspired other groups, like the Brown Berets and the Young Lords. [5, 6, 7, 8]
- Context: While not a traditional manifesto, Martin Luther King Jr.'s open letter, written while he was incarcerated for protesting segregation, functions as a powerful declaration of civil rights principles.
- Argument: King defends the strategy of nonviolent resistance, arguing that it is a moral and effective tool for social change. He famously declared that "injustice anywhere is a threat to justice everywhere".
- Influence: This document rallied support for the civil rights movement and remains a foundational text on civil disobedience. [9, 10, 11, 12, 13]
The New Left and student movements
- Context: This manifesto was adopted by the newly formed student activist group, Students for a Democratic Society (SDS), at a convention in Port Huron, Michigan. Written primarily by Tom Hayden, it captured the disillusionment of young people with the established political system.
- Key Concepts:
- Participatory Democracy: The document's central idea called for a more democratic society in which individuals have a greater say in the decisions affecting their lives.
- Rejection of the Status Quo: It criticized racial bigotry, Cold War politics, and the apathy of the older generation.
- Influence: The Port Huron Statement was a foundational text for the New Left and greatly influenced student activism and the anti-war movement. [14, 15, 16, 17, 18]
- Context: This position paper was the founding document of the radical Weatherman faction of SDS, which believed that nonviolent tactics were failing.
- Ideology: It espoused a Marxist-Leninist view of the U.S. as an imperialist power and called for a violent, revolutionary movement to ally with anti-imperialist forces and black liberation movements.
- Tactics: The manifesto advocated for creating a clandestine, revolutionary party and engaging in urban guerrilla warfare and bombings. [19, 20, 21, 22]
The feminist movement
- Context: In 1966, the National Organization for Women (NOW) was founded by prominent feminists like Betty Friedan. The organization's statement outlined its reformist approach to achieving gender equality.
- Demands: NOW called for equal rights for women, including economic opportunities, fair hiring practices, and equal representation in all aspects of American society. [2, 23, 24, 25, 26]
- Context: Radical feminist Valerie Solanas self-published this controversial and provocative text just before she shot Andy Warhol in 1968.
- Key Arguments: The manifesto argues that men are biologically inferior and have ruined the world. It suggests forming a group called SCUM (Society for Cutting Up Men) to overthrow society and eliminate the male sex.
- Controversy and Interpretation: The document was dismissed by many as the ranting of a mentally unstable individual, while others viewed it as a radical satire exposing patriarchal rage. It remains a polarizing text that fueled debates within the women's movement. [27, 28, 29]
Farmworkers' movement
- Context: As a leader of the United Farm Workers (UFW), Chávez used nonviolent tactics to organize farmworkers and achieve better working conditions. His speeches and writings functioned as manifestos for the movement.
- Key Principles:
- Nonviolence: Chávez advocated for the power of nonviolence and sacrifice, inspired by Martin Luther King Jr. and Mahatma Gandhi.
- "La Causa": His movement, "The Cause," advocated for union recognition, fair wages, and protection from dangerous pesticides for farmworkers.
- Influence: Chávez's use of manifestos, speeches, and public statements drew national attention to the plight of farmworkers and rallied support from students, artists, and political figures. [30, 31, 32, 33, 34]
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searched on
- Rejection of authority: The counterculture, of which hippies were a part, rejected the "Establishment" and traditional authorities. Yoga provided a practice that was distinctly different from Western institutions, offering an alternative way of living and thinking.
- Spiritual seeking: Young people were drawn to Eastern philosophies, including yoga, as a way to find meaning and achieve "cosmic consciousness" outside of mainstream religion. Yoga was part of a broader interest in meditation, Eastern mysticism, and personal potential that moved many away from organized religion.
- Lifestyle and community: Yoga became integrated into the counterculture lifestyle, which included vegetarianism, eco-friendly practices, and intentional communities (communes). For instance, Swami Satchidananda opened the 1969 Woodstock festival, symbolizing the integration of yoga and Eastern spirituality with the counterculture's embrace of peace and love.
- Influence of key figures:
- Swami Satchidananda: He founded the Integral Yoga Institute in New York in 1966 and played a prominent role at Woodstock, bringing his teachings to a massive audience.
- B.K.S. Iyengar: His influential book Light on Yoga was published in the US in 1966, becoming a foundational text for serious practitioners and shaping the practice of yoga for many Americans.
- Yogi Bhajan: His yoga sessions were a part of the counterculture, with photographs showing him with groups on communes in New Mexico.
- Broader social context: The growth of yoga interest in the 1960s occurred alongside, and was often intertwined with, other movements that challenged the status quo, such as the Civil Rights Movement, the anti-war movement, and the nascent women's and gay rights movements. Yoga was a part of this larger wave of social and spiritual questioning. [1, 2, 3, 4, 7, 8, 9, 10, 11]
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But I also find Yoga meditation unifying too regarding an inner releasing actions and explorations and consciousness.
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I continue to get these AI and Robotics + researchers' academic papers in my email box, compiled by UC Berkeley Prof Anca Dragan (originally from Germany) ... and which related papers will be helpful in developing MIT OCW-centric wiki World University and School's Robotics and Artificial Intelligence and Machine Learning and Large Language Models in all 200 countries and in all 7159 known living languages ... and in a #RealisticVirtualEarth #ForRobotics and #ForEverything ...
https://scholar.google.com/citations?user=UgHB5oAAAAAJ&hl=en
Title | Cited by | Year |
---|---|---|
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context https://arxiv.org/abs/2403.05530 | 2766* | 2024 |
Gemma 2: Improving open language models at a practical size G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ... arXiv preprint arXiv:2408.00118 | 1375 | 2024 |
Legibility and predictability of robot motion AD Dragan, KCT Lee, SS Srinivasa 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 981 | 2013 |
Cooperative Inverse Reinforcement Learning D Hadfield-Menell, A Dragan, P Abbeel, S Russell Neural Information Processing Systems (NIPS) | 965 | 2016 |
CHOMP: Covariant Hamiltonian Optimization for Motion Planning M Zucker, N Ratliff, AD Dragan, M Pivtoraiko, M Klingensmith, C Dellin, ... International Journal of Robotics Research | 957 | 2013 |
Open problems and fundamental limitations of reinforcement learning from human feedback S Casper, X Davies, C Shi, TK Gilbert, J Scheurer, J Rando, R Freedman, ... arXiv preprint arXiv:2307.15217 | 754 | 2023 |
Planning for autonomous cars that leverage effects on human actions. D Sadigh, S Sastry, SA Seshia, AD Dragan Robotics: Science and systems 2, 1-9 | 696 | 2016 |
On the utility of learning about humans for human-ai coordination M Carroll, R Shah, MK Ho, T Griffiths, S Seshia, P Abbeel, A Dragan Advances in neural information processing systems 32 | 589 | 2019 |
Inverse reward design D Hadfield-Menell, S Milli, P Abbeel, SJ Russell, A Dragan Advances in neural information processing systems 30 | 574 | 2017 |
A policy-blending formalism for shared control AD Dragan, SS Srinivasa The International Journal of Robotics Research 32 (7), 790-805 | 495 | 2013 |
Active preference-based learning of reward functions D Sadigh, AD Dragan, S Sastry, S Seshia RSS | 476 | 2017 |
Effects of robot motion on human-robot collaboration AD Dragan, S Bauman, J Forlizzi, SS Srinivasa Proceedings of the tenth annual ACM/IEEE international conference on human … | 436 | 2015 |
Managing extreme AI risks amid rapid progress Y Bengio, G Hinton, A Yao, D Song, P Abbeel, T Darrell, YN Harari, ... Science 384 (6698), 842-845 | 424 | 2024 |
SQIL: imitation learning via regularized behavioral cloning S Reddy, AD Dragan, S Levine arXiv preprint arXiv:1905.11108 2 (5) | 414* | 2019 |
On stochastic optimal control and reinforcement learning by approximate inference K Rawlik, M Toussaint, S Vijayakumar Proceedings of Robotics: Science and Systems VIII | 401 | 2012 |
Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities G Comanici, E Bieber, M Schaekermann, I Pasupat, N Sachdeva, I Dhillon, ... arXiv preprint arXiv:2507.06261 | 382 | 2025 |
Toward seamless human-robot handovers K Strabala, MK Lee, A Dragan, J Forlizzi, SS Srinivasa, M Cakmak, ... Journal of Human-Robot Interaction 2 (1), 112-132 | 367 | 2013 |
Hierarchical game-theoretic planning for autonomous vehicles JF Fisac, E Bronstein, E Stefansson, D Sadigh, SS Sastry, AD Dragan 2019 International conference on robotics and automation (ICRA), 9590-9596 | 351 | 2019 |
Dart: Noise injection for robust imitation learning M Laskey, J Lee, R Fox, A Dragan, K Goldberg Conference on robot learning, 143-156 | 329 | 2017 |
Information gathering actions over human internal state D Sadigh, SS Sastry, SA Seshia, A Dragan 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 260 | 2016 |
Planning for cars that coordinate with people: leveraging effects on human actions for planning and active information gathering over human internal state D Sadigh, N Landolfi, SS Sastry, SA Seshia, AD Dragan Autonomous Robots 42 (7), 1405-1426 | 253 | 2018 |
Reward-rational (implicit) choice: A unifying formalism for reward learning HJ Jeon, S Milli, A Dragan Advances in Neural Information Processing Systems 33, 4415-4426 | 247 | 2020 |
The social cost of strategic classification S Milli, J Miller, AD Dragan, M Hardt Proceedings of the conference on fairness, accountability, and transparency … | 245 | 2019 |
Do you want your autonomous car to drive like you? C Basu, Q Yang, D Hungerman, M Singhal, AD Dragan Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot … | 242 | 2017 |
Efficient iterative linear-quadratic approximations for nonlinear multi-player general-sum differential games D Fridovich-Keil, E Ratner, L Peters, AD Dragan, CJ Tomlin 2020 IEEE international conference on robotics and automation (ICRA), 1475-1481 | 241 | 2020 |
Generating legible motion A Dragan, S Srinivasa Carnegie Mellon University | 241 | 2013 |
Model reconstruction from model explanations S Milli, L Schmidt, AD Dragan, M Hardt Proceedings of the Conference on Fairness, Accountability, and Transparency, 1-9 | 240 | 2019 |
The off-switch game D Hadfield-Menell, A Dragan, P Abbeel, S Russell IJCAI | 239 | 2017 |
Shared autonomy via deep reinforcement learning S Reddy, AD Dragan, S Levine arXiv preprint arXiv:1802.01744 | 235 | 2018 |
Automatically auditing large language models via discrete optimization E Jones, A Dragan, A Raghunathan, J Steinhardt International Conference on Machine Learning, 15307-15329 | 222 | 2023 |
Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2 T Lieberum, S Rajamanoharan, A Conmy, L Smith, N Sonnerat, V Varma, ... arXiv preprint arXiv:2408.05147 | 212 | 2024 |
Enabling Robots to Communicate their Objectives SH Huang, D Held, P Abbeel, AD Dragan RSS | 207 | 2017 |
Learning robot objectives from physical human interaction A Bajcsy, DP Losey, MK O’malley, AD Dragan Conference on robot learning, 217-226 | 202 | 2017 |
Formalizing assistive teleoperation AD Dragan, SS Srinivasa Robotics: Science and Systems | 199 | 2012 |
Probabilistically safe robot planning with confidence-based human predictions JF Fisac, A Bajcsy, SL Herbert, D Fridovich-Keil, S Wang, CJ Tomlin, ... arXiv preprint arXiv:1806.00109 | 178 | 2018 |
Confidence-aware motion prediction for real-time collision avoidance1 D Fridovich-Keil, A Bajcsy, JF Fisac, SL Herbert, S Wang, AD Dragan, ... The International Journal of Robotics Research 39 (2-3), 250-265 | 177 | 2020 |
Expressing robot incapability M Kwon, SH Huang, AD Dragan Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot … | 177 | 2018 |
Establishing appropriate trust via critical states SH Huang, K Bhatia, P Abbeel, AD Dragan 2018 IEEE/RSJ international conference on intelligent robots and systems … | 172 | 2018 |
Herb 2.0: Lessons learned from developing a mobile manipulator for the home SS Srinivasa, D Berenson, M Cakmak, A Collet, MR Dogar, AD Dragan, ... Proceedings of the IEEE 100 (8), 2410-2428 | 166 | 2012 |
B-pref: Benchmarking preference-based reinforcement learning K Lee, L Smith, A Dragan, P Abbeel arXiv preprint arXiv:2111.03026 | 160 | 2021 |
Physics-based grasp planning through clutter M Dogar, K Hsiao, M Ciocarlie, S Srinivasa MIT Press 8, 57-64 | 160 | 2012 |
Deliberate delays during robot-to-human handovers improve compliance with gaze communication H Admoni, A Dragan, SS Srinivasa, B Scassellati Proceedings of the 2014 ACM/IEEE international conference on Human-robot … | 153 | 2014 |
Where do you think you're going?: Inferring beliefs about dynamics from behavior S Reddy, A Dragan, S Levine Advances in Neural Information Processing Systems 31 | 139 | 2018 |
Learning from physical human corrections, one feature at a time A Bajcsy, DP Losey, MK O'Malley, AD Dragan Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot … | 129 | 2018 |
Managing ai risks in an era of rapid progress Y Bengio, G Hinton, A Yao, D Song, P Abbeel, YN Harari, YQ Zhang, ... arXiv preprint arXiv:2310.17688, 18 | 119 | 2023 |
Pragmatic-pedagogic value alignment JF Fisac, MA Gates, JB Hamrick, C Liu, D Hadfield-Menell, ... Robotics research: the 18th international symposium Isrr, 49-57 | 111 | 2019 |
Perceived robot capability E Cha, AD Dragan, SS Srinivasa 2015 24th IEEE International Symposium on Robot and Human Interactive … | 109 | 2015 |
Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations M Laskey, J Lee, C Chuck, D Gealy, W Hsieh, FT Pokorny, AD Dragan, ... 2016 IEEE international conference on automation science and engineering … | 107 | 2016 |
Shiv: Reducing supervisor burden in dagger using support vectors for efficient learning from demonstrations in high dimensional state spaces M Laskey, S Staszak, WYS Hsieh, J Mahler, FT Pokorny, AD Dragan, ... 2016 IEEE International Conference on Robotics and Automation (ICRA), 462-469 | 106 | 2016 |
Courteous autonomous cars L Sun, W Zhan, M Tomizuka, AD Dragan 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 105 | 2018 |
Integrating human observer inferences into robot motion planning A Dragan, S Srinivasa Autonomous Robots 37 (4), 351-368 | 105 | 2014 |
Manipulation planning with goal sets using constrained trajectory optimization AD Dragan, ND Ratliff, SS Srinivasa 2011 IEEE International Conference on Robotics and Automation, 4582-4588 | 100 | 2011 |
A scalable framework for real-time multi-robot, multi-human collision avoidance A Bajcsy, SL Herbert, D Fridovich-Keil, JF Fisac, S Deglurkar, AD Dragan, ... 2019 international conference on robotics and automation (ICRA), 936-943 | 99 | 2019 |
Learning human objectives by evaluating hypothetical behavior S Reddy, A Dragan, S Levine, S Legg, J Leike International conference on machine learning, 8020-8029 | 98 | 2020 |
Learning a prior over intent via meta-inverse reinforcement learning K Xu, E Ratner, A Dragan, S Levine, C Finn International conference on machine learning, 6952-6962 | 91 | 2019 |
Legible robot pointing RM Holladay, AD Dragan, SS Srinivasa The 23rd IEEE International Symposium on robot and human interactive … | 91 | 2014 |
Evaluating frontier models for dangerous capabilities M Phuong, M Aitchison, E Catt, S Cogan, A Kaskasoli, V Krakovna, ... arXiv preprint arXiv:2403.13793 | 90 | 2024 |
Should Robots be Obedient? S Milli, D Hadfield-Menell, A Dragan, S Russell IJCAI | 89 | 2017 |
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations M Laskey, C Chuck, J Lee, J Mahler, S Krishnan, K Jamieson, A Dragan, ... ICRA | 87 | 2016 |
On the feasibility of learning, rather than assuming, human biases for reward inference R Shah, N Gundotra, P Abbeel, A Dragan International conference on machine learning, 5670-5679 | 85 | 2019 |
Goal inference improves objective and perceived performance in human-robot collaboration C Liu, JB Hamrick, JF Fisac, AD Dragan, JK Hedrick, SS Sastry, ... arXiv preprint arXiv:1802.01780 | 85 | 2018 |
Benchmarks and algorithms for offline preference-based reward learning D Shin, AD Dragan, DS Brown arXiv preprint arXiv:2301.01392 | 84 | 2023 |
Functional gradient motion planning in reproducing kernel hilbert spaces Z Marinho, A Dragan, A Byravan, B Boots, S Srinivasa, G Gordon arXiv preprint arXiv:1601.03648 | 79 | 2016 |
Learning the communication of intent prior to physical collaboration K Strabala, MK Lee, A Dragan, J Forlizzi, SS Srinivasa 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human … | 78 | 2012 |
Safety assurances for human-robot interaction via confidence-aware game-theoretic human models R Tian, L Sun, A Bajcsy, M Tomizuka, AD Dragan 2022 International Conference on Robotics and Automation (ICRA), 11229-11235 | 77 | 2022 |
Preferences implicit in the state of the world R Shah, D Krasheninnikov, J Alexander, P Abbeel, A Dragan arXiv preprint arXiv:1902.04198 | 77 | 2019 |
Movement primitives via optimization AD Dragan, K Muelling, JA Bagnell, SS Srinivasa 2015 IEEE International Conference on Robotics and Automation (ICRA), 2339-2346 | 76 | 2015 |
Less is more: Rethinking probabilistic models of human behavior A Bobu, DRR Scobee, JF Fisac, SS Sastry, AD Dragan Proceedings of the 2020 acm/ieee international conference on human-robot … | 75 | 2020 |
Expressive robot motion timing A Zhou, D Hadfield-Menell, A Nagabandi, AD Dragan Proceedings of the 2017 ACM/IEEE international conference on human-robot … | 74 | 2017 |
Imagen 3 J Baldridge, J Bauer, M Bhutani, N Brichtova, A Bunner, L Castrejon, ... arXiv preprint arXiv:2408.07009 | 73 | 2024 |
Engagement, user satisfaction, and the amplification of divisive content on social media S Milli, M Carroll, Y Wang, S Pandey, S Zhao, AD Dragan PNAS nexus 4 (3), pgaf062 | 72 | 2025 |
Familiarization to robot motion A Dragan, S Srinivasa Proceedings of the 2014 ACM/IEEE international conference on Human-robot … | 71 | 2014 |
Accelerating human learning with deep reinforcement learning S Reddy, S Levine, A Dragan NIPS workshop: teaching machines, robots, and humans 9, 5-9 | 70 | 2017 |
Confronting reward model overoptimization with constrained rlhf T Moskovitz, AK Singh, DJ Strouse, T Sandholm, R Salakhutdinov, ... arXiv preprint arXiv:2310.04373 | 69 | 2023 |
On the utility of model learning in hri R Choudhury, G Swamy, D Hadfield-Menell, AD Dragan 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 69 | 2019 |
Learning to model the world with language J Lin, Y Du, O Watkins, D Hafner, P Abbeel, D Klein, A Dragan arXiv preprint arXiv:2308.01399 | 68 | 2023 |
Learning from richer human guidance: Augmenting comparison-based learning with feature queries C Basu, M Singhal, AD Dragan Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot … | 68 | 2018 |
Causal confusion and reward misidentification in preference-based reward learning J Tien, JZY He, Z Erickson, AD Dragan, DS Brown arXiv preprint arXiv:2204.06601 | 66 | 2022 |
Physical interaction as communication: Learning robot objectives online from human corrections DP Losey, A Bajcsy, MK O’Malley, AD Dragan The International Journal of Robotics Research 41 (1), 20-44 | 66 | 2022 |
Estimating and penalizing induced preference shifts in recommender systems MD Carroll, A Dragan, S Russell, D Hadfield-Menell International Conference on Machine Learning, 2686-2708 | 63 | 2022 |
Inferring rewards from language in context J Lin, D Fried, D Klein, A Dragan arXiv preprint arXiv:2204.02515 | 63 | 2022 |
Feature expansive reward learning: Rethinking human input A Bobu, M Wiggert, C Tomlin, AD Dragan Proceedings of the 2021 ACM/IEEE international conference on human-robot … | 62 | 2021 |
Scaled autonomy: Enabling human operators to control robot fleets G Swamy, S Reddy, S Levine, AD Dragan 2020 IEEE International Conference on Robotics and Automation (ICRA), 5942-5948 | 62 | 2020 |
Translating Neuralese J Andreas, A Dragan, D Klein ACL | 61 | 2017 |
The assistive multi-armed bandit L Chan, D Hadfield-Menell, S Srinivasa, A Dragan 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 60 | 2019 |
Teleoperation with intelligent and customizable interfaces AD Dragan, SS Srinivasa, KCT Lee Journal of Human-Robot Interaction 2 (2), 33-57 | 60 | 2013 |
Value alignment verification DS Brown, J Schneider, A Dragan, S Niekum International Conference on Machine Learning, 1105-1115 | 59 | 2021 |
Quantifying hypothesis space misspecification in learning from human–robot demonstrations and physical corrections A Bobu, A Bajcsy, JF Fisac, S Deglurkar, AD Dragan IEEE Transactions on Robotics 36 (3), 835-854 | 59 | 2020 |
Learning from experience in manipulation planning: Setting the right goals AD Dragan, GJ Gordon, SS Srinivasa ISRR, 309-326 | 59* | 2012 |
Ave: Assistance via empowerment Y Du, S Tiomkin, E Kiciman, D Polani, P Abbeel, A Dragan Advances in Neural Information Processing Systems 33, 4560-4571 | 55 | 2020 |
Deceptive robot motion: synthesis, analysis and experiments A Dragan, R Holladay, S Srinivasa Autonomous Robots 39 (3), 331-345 | 55 | 2015 |
An Analysis of Deceptive Robot Motion AD Dragan, R Holladay, SS Srinivasa Robotics Science and Systems | 55 | 2014 |
Robot planning with mathematical models of human state and action AD Dragan arXiv preprint arXiv:1705.04226 | 52 | 2017 |
Simplifying reward design through divide-and-conquer E Ratner, D Hadfield-Menell, AD Dragan arXiv preprint arXiv:1806.02501 | 50 | 2018 |
Implicitly assisting humans to choose good grasps in robot to human handovers A Bestick, R Bajcsy, AD Dragan International symposium on experimental robotics, 341-354 | 48 | 2016 |
The effect of modeling human rationality level on learning rewards from multiple feedback types GR Ghosal, M Zurek, DS Brown, AD Dragan Proceedings of the AAAI Conference on Artificial Intelligence 37 (5), 5983-5992 | 47 | 2023 |
The boltzmann policy distribution: Accounting for systematic suboptimality in human models C Laidlaw, A Dragan arXiv preprint arXiv:2204.10759 | 47 | 2022 |
Inducing structure in reward learning by learning features A Bobu, M Wiggert, C Tomlin, AD Dragan The International Journal of Robotics Research 41 (5), 497-518 | 47 | 2022 |
A hamilton-jacobi reachability-based framework for predicting and analyzing human motion for safe planning S Bansal, A Bajcsy, E Ratner, AD Dragan, CJ Tomlin 2020 IEEE International Conference on Robotics and Automation (ICRA), 7149-7155 | 47 | 2020 |
Generating plans that predict themselves JF Fisac, C Liu, JB Hamrick, S Sastry, JK Hedrick, TL Griffiths, AD Dragan Algorithmic Foundations of Robotics XII: Proceedings of the Twelfth Workshop … | 47 | 2020 |
An efficient, generalized bellman update for cooperative inverse reinforcement learning D Malik, M Palaniappan, J Fisac, D Hadfield-Menell, S Russell, A Dragan International Conference on Machine Learning, 3394-3402 | 46 | 2018 |
Learning human ergonomic preferences for handovers A Bestick, R Pandya, R Bajcsy, AD Dragan 2018 IEEE international conference on robotics and automation (ICRA), 3257-3264 | 46 | 2018 |
Active comparison based learning incorporating user uncertainty and noise R Holladay, S Javdani, A Dragan, S Srinivasa RSS Workshop on Model Learning for Human-Robot Communication | 46 | 2016 |
Viewpoint-based legibility optimization S Nikolaidis, A Dragan, S Srinivasa Human-Robot Interaction (HRI), 2016 11th ACM/IEEE International Conference … | 46* | 2016 |
Evaluating the robustness of collaborative agents P Knott, M Carroll, S Devlin, K Ciosek, K Hofmann, AD Dragan, R Shah arXiv preprint arXiv:2101.05507 | 45 | 2021 |
Learning under misspecified objective spaces A Bobu, A Bajcsy, JF Fisac, AD Dragan Conference on robot learning, 796-805 | 45 | 2018 |
Uni [mask]: Unified inference in sequential decision problems M Carroll, O Paradise, J Lin, R Georgescu, M Sun, D Bignell, S Milani, ... Advances in neural information processing systems 35, 35365-35378 | 43 | 2022 |
Benefits of assistance over reward learning R Shah, P Freire, N Alex, R Freedman, D Krasheninnikov, L Chan, ... | 40 | 2020 |
Bridging rl theory and practice with the effective horizon C Laidlaw, SJ Russell, A Dragan Advances in Neural Information Processing Systems 36, 58953-59007 | 39 | 2023 |
Goal representations for instruction following: A semi-supervised language interface to control V Myers, AW He, K Fang, HR Walke, P Hansen-Estruch, CA Cheng, ... Conference on Robot Learning, 3894-3908 | 39 | 2023 |
Learning representations that enable generalization in assistive tasks JZY He, Z Erickson, DS Brown, A Raghunathan, A Dragan Conference on Robot Learning, 2105-2114 | 39 | 2023 |
Situational confidence assistance for lifelong shared autonomy M Zurek, A Bobu, DS Brown, AD Dragan 2021 IEEE International Conference on Robotics and Automation (ICRA), 2783-2789 | 37 | 2021 |
A robust control framework for human motion prediction A Bajcsy, S Bansal, E Ratner, CJ Tomlin, AD Dragan IEEE Robotics and Automation Letters 6 (1), 24-31 | 37 | 2020 |
Inferring and assisting with constraints in shared autonomy N Mehr, R Horowitz, AD Dragan 2016 IEEE 55th Conference on Decision and Control (CDC), 6689-6696 | 36 | 2016 |
Ai alignment with changing and influenceable reward functions M Carroll, D Foote, A Siththaranjan, S Russell, A Dragan arXiv preprint arXiv:2405.17713 | 35 | 2024 |
Aligning robot and human representations A Bobu, A Peng, P Agrawal, J Shah, AD Dragan arXiv preprint arXiv:2302.01928 | 35 | 2023 |
Learning to influence human behavior with offline reinforcement learning J Hong, S Levine, A Dragan Advances in neural information processing systems 36, 36094-36105 | 34 | 2023 |
Twitter's algorithm: Amplifying anger, animosity, and affective polarization S Milli, M Carroll, S Pandey, Y Wang, AD Dragan CoRR | 34 | 2023 |
Explainable robotic systems MMA De Graaf, BF Malle, A Dragan, T Ziemke Companion of the 2018 ACM/IEEE International Conference on Human-Robot … | 33 | 2018 |
Zero-shot goal-directed dialogue via rl on imagined conversations J Hong, S Levine, A Dragan arXiv preprint arXiv:2311.05584 | 32 | 2023 |
Human irrationality: both bad and good for reward inference L Chan, A Critch, A Dragan arXiv preprint arXiv:2111.06956 | 32 | 2021 |
Policy gradient bayesian robust optimization for imitation learning Z Javed, DS Brown, S Sharma, J Zhu, A Balakrishna, M Petrik, A Dragan, ... International Conference on Machine Learning, 4785-4796 | 31 | 2021 |
An approach to technical agi safety and security R Shah, A Irpan, AM Turner, A Wang, A Conmy, D Lindner, ... arXiv preprint arXiv:2504.01849 | 30 | 2025 |
First contact: Unsupervised human-machine co-adaptation via mutual information maximization S Reddy, S Levine, A Dragan Advances in Neural Information Processing Systems 35, 31542-31556 | 30 | 2022 |
Estimating and penalizing preference shift in recommender systems M Carroll, D Hadfield-Menell, S Russell, A Dragan Proceedings of the 15th ACM Conference on Recommender Systems, 661-667 | 30 | 2021 |
Aligning human and robot representations A Bobu, A Peng, P Agrawal, JA Shah, AD Dragan Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot … | 29 | 2024 |
Towards modeling and influencing the dynamics of human learning R Tian, M Tomizuka, AD Dragan, A Bajcsy Proceedings of the 2023 ACM/IEEE international conference on human-robot … | 29 | 2023 |
On the sensitivity of reward inference to misspecified human models J Hong, K Bhatia, A Dragan arXiv preprint arXiv:2212.04717 | 29 | 2022 |
Analyzing human models that adapt online A Bajcsy, A Siththaranjan, CJ Tomlin, AD Dragan 2021 IEEE International Conference on Robotics and Automation (ICRA), 2754-2760 | 29 | 2021 |
Optimal cost design for model predictive control A Jain, L Chan, DS Brown, AD Dragan Learning for Dynamics and Control, 1205-1217 | 29 | 2021 |
Variational Bayesian optimization for runtime risk-sensitive control S Kuindersma, R Grupen, A Barto Robotics: Science and systems viii, 201-208 | 29 | 2012 |
Sirl: Similarity-based implicit representation learning A Bobu, Y Liu, R Shah, DS Brown, AD Dragan Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot … | 28 | 2023 |
Control for Societal-Scale Challenges: Roadmap 2030 A Alleyne, F Allgöwer, AD Ames, S Amin, J Anderson, AM Annaswamy, ... IEEE Control Systems Society Publication | 28 | 2023 |
The MineRL BASALT competition on learning from human feedback R Shah, C Wild, SH Wang, N Alex, B Houghton, W Guss, S Mohanty, ... arXiv preprint arXiv:2107.01969 | 28 | 2021 |
Exploiting passive dynamics with variable stiffness actuation in robot brachiation J Nakanishi, S Vijayakumar Robotics: Science and systems 8, 305 | 28 | 2013 |
On targeted manipulation and deception when optimizing llms for user feedback M Williams, M Carroll, A Narang, C Weisser, B Murphy, A Dragan arXiv preprint arXiv:2411.02306 | 27 | 2024 |
Learning temporal distances: Contrastive successor features can provide a metric structure for decision-making V Myers, C Zheng, A Dragan, S Levine, B Eysenbach arXiv preprint arXiv:2406.17098 | 27 | 2024 |
Asha: Assistive teleoperation via human-in-the-loop reinforcement learning S Chen, J Gao, S Reddy, G Berseth, AD Dragan, S Levine 2022 International Conference on Robotics and Automation (ICRA), 7505-7512 | 26 | 2022 |
Literal or pedagogic human? analyzing human model misspecification in objective learning S Milli, AD Dragan Uncertainty in artificial intelligence, 925-934 | 26 | 2020 |
Cost functions for robot motion style A Zhou, AD Dragan 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 26 | 2018 |
Special issue on learning for human–robot collaboration L Rozo, HB Amor, S Calinon, A Dragan, D Lee Autonomous Robots 42 (5), 953-956 | 26 | 2018 |
Online customization of teleoperation interfaces AD Dragan, SS Srinivasa 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human … | 26 | 2012 |
Toward grounded commonsense reasoning M Kwon, H Hu, V Myers, S Karamcheti, A Dragan, D Sadigh 2024 IEEE International Conference on Robotics and Automation (ICRA), 5463-5470 | 25 | 2024 |
Offline preference-based apprenticeship learning D Shin, DS Brown, AD Dragan arXiv preprint arXiv:2107.09251 | 24 | 2021 |
On complementing end-to-end human behavior predictors with planning L Sun, X Jia, AD Dragan arXiv preprint arXiv:2103.05661 | 23 | 2021 |
Choice set misspecification in reward inference R Freedman, R Shah, A Dragan arXiv preprint arXiv:2101.07691 | 23 | 2021 |
Legible robot motion planning AD Dragan Carnegie Mellon University | 23 | 2015 |
Chain of thought monitorability: A new and fragile opportunity for ai safety T Korbak, M Balesni, E Barnes, Y Bengio, J Benton, J Bloom, M Chen, ... arXiv preprint arXiv:2507.11473 | 21 | 2025 |
Assisted perception: optimizing observations to communicate state S Reddy, S Levine, A Dragan Conference on robot learning, 748-764 | 21 | 2021 |
Nonverbal robot feedback for human teachers SH Huang, I Huang, R Pandya, AD Dragan arXiv preprint arXiv:1911.02320 | 21 | 2019 |
Assitive Teleoperation for Manipulation Tasks AD Dragan, SS Srinivasa | 20 | 2012 |
Preventing reward hacking with occupancy measure regularization C Laidlaw, S Singhal, A Dragan | 18 | 2023 |
Toward grounded social reasoning M Kwon, H Hu, V Myers, S Karamcheti, A Dragan, D Sadigh arXiv preprint arXiv:2306.08651 | 18 | 2023 |
Pragmatic image compression for human-in-the-loop decision-making S Reddy, A Dragan, S Levine Advances in Neural Information Processing Systems 34, 26499-26510 | 18 | 2021 |
Adversaries can misuse combinations of safe models E Jones, A Dragan, J Steinhardt arXiv preprint arXiv:2406.14595 | 17 | 2024 |
Correlated proxies: A new definition and improved mitigation for reward hacking C Laidlaw, S Singhal, A Dragan arXiv preprint arXiv:2403.03185 | 17 | 2024 |
Optimal behavior prior: Data-efficient human models for improved human-ai collaboration M Yang, M Carroll, A Dragan arXiv preprint arXiv:2211.01602 | 17 | 2022 |
Teaching robots to span the space of functional expressive motion A Sripathy, A Bobu, Z Li, K Sreenath, DS Brown, AD Dragan 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 17 | 2022 |
Preference learning along multiple criteria: A game-theoretic perspective K Bhatia, A Pananjady, P Bartlett, A Dragan, MJ Wainwright Advances in neural information processing systems 33, 7413-7424 | 17 | 2020 |
Learning from extrapolated corrections JY Zhang, AD Dragan 2019 International Conference on Robotics and Automation (ICRA), 7034-7040 | 17 | 2019 |
Social cohesion in autonomous driving NC Landolfi, AD Dragan 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 17 | 2018 |
Assisted robust reward design JZY He, AD Dragan arXiv preprint arXiv:2111.09884 | 16 | 2021 |
How to be helpful to multiple people at once V Gates, TL Griffiths, AD Dragan Cognitive science 44 (6), e12841 | 16 | 2020 |
Learning optimal advantage from preferences and mistaking it for reward WB Knox, S Hatgis-Kessell, SO Adalgeirsson, S Booth, A Dragan, P Stone, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (9), 10066 … | 15 | 2024 |
A study of causal confusion in preference-based reward learning J Tien, JZY He, Z Erickson, A Dragan, DS Brown ICML 2022: Workshop on Spurious Correlations, Invariance and Stability | 15 | 2022 |
Human-AI learning performance in multi-armed bandits R Pandya, SH Huang, D Hadfield-Menell, AD Dragan Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 369-375 | 15 | 2019 |
Trajectory improvement and reward learning from comparative language feedback Z Yang, M Jun, J Tien, SJ Russell, A Dragan, E Bıyık arXiv preprint arXiv:2410.06401 | 14 | 2024 |
Explaining robot policies O Watkins, S Huang, J Frost, K Bhatia, E Weiner, P Abbeel, T Darrell, ... Applied AI Letters 2 (4), e52 | 13 | 2021 |
Experiments with Balancing on Irregular Terrains using the Dreamer Mobile Humanoid Robot. L Sentis, J Petersen, R Philippsen Robotics: Science and Systems | 13 | 2012 |
Introduction to the special issue on explainable robotic systems MMA De Graaf, A Dragan, BF Malle, T Ziemke ACM Transactions on Human-Robot Interaction (THRI) 10 (3), 1-4 | 12 | 2021 |
X2T: Training an x-to-text typing interface with online learning from user feedback J Gao, S Reddy, G Berseth, N Hardy, N Natraj, K Ganguly, AD Dragan, ... arXiv preprint arXiv:2203.02072 | 11 | 2022 |
Effects of robot capability on user acceptance E Cha, AD Dragan, SS Srinivasa 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 11 | 2013 |
Cos: Enhancing personalization and mitigating bias with context steering JZY He, S Pandey, ML Schrum, A Dragan arXiv preprint arXiv:2405.01768 | 10 | 2024 |
Dynamically switching human prediction models for efficient planning A Sripathy, A Bobu, DS Brown, AD Dragan 2021 IEEE International Conference on Robotics and Automation (ICRA), 3495-3501 | 10 | 2021 |
Bayesian robustness: A nonasymptotic viewpoint K Bhatia, YA Ma, AD Dragan, PL Bartlett, MI Jordan arXiv preprint arXiv:1907.11826 | 10 | 2019 |
Feature-based prediction of trajectories for socially compliant navigation P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 10 | 2013 |
When your ais deceive you: Challenges with partial observability of human evaluators in reward learning L Lang, D Foote, S Russell, AD Dragan, E Jenner, S Emmons CoRR | 9 | 2024 |
Configuration space metrics HJ Jeon, AD Dragan 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 9 | 2018 |
Collaborative manipulation: new challenges for robotics and hri AD Dragan, AL Thomaz, SS Srinivasa 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 9 | 2013 |
Distributed Approximation of Joint Measurement Distributions Using Mixtures of Gaussians. BJ Julian, SL Smith, D Rus Robotics: Science and Systems | 9 | 2012 |
Q-sft: Q-learning for language models via supervised fine-tuning J Hong, A Dragan, S Levine arXiv preprint arXiv:2411.05193 | 8 | 2024 |
Towards flexible inference in sequential decision problems via bidirectional transformers M Carroll, J Lin, O Paradise, R Georgescu, M Sun, D Bignell, S Milani, ... arXiv preprint arXiv:2204.13326 | 8 | 2022 |
Learning what to do by simulating the past D Lindner, R Shah, P Abbeel, A Dragan arXiv preprint arXiv:2104.03946 | 8 | 2021 |
Learning to assist humans without inferring rewards V Myers, E Ellis, S Levine, B Eysenbach, A Dragan Advances in Neural Information Processing Systems 37, 71540-71567 | 7 | 2024 |
Offline rl with observation histories: Analyzing and improving sample complexity J Hong, A Dragan, S Levine arXiv preprint arXiv:2310.20663 | 7 | 2023 |
Time-efficient reward learning via visually assisted cluster ranking D Zhang, M Carroll, A Bobu, A Dragan arXiv preprint arXiv:2212.00169 | 7 | 2022 |
On complementing end-to-end human motion predictors with planning L Sun, X Jia, AD Dragan 2021 Robotics: Science and Systems (RSS) | 7 | 2021 |
Effects of speech on perceived capability E Cha, A Dragan, J Forlizzi, S Srinivasa Proceedings of the 2014 ACM/IEEE international conference on Human-robot … | 7 | 2014 |
When your AIs deceive you: Challenges of partial observability in reinforcement learning from human feedback L Lang, D Foote, SJ Russell, A Dragan, E Jenner, S Emmons Advances in Neural Information Processing Systems 37, 93240-93299 | 6 | 2024 |
A generalized acquisition function for preference-based reward learning E Ellis, GR Ghosal, SJ Russell, A Dragan, E Bıyık 2024 IEEE International Conference on Robotics and Automation (ICRA), 2814-2821 | 6 | 2024 |
The Effective Horizon Explains Deep RL Performance in Stochastic Environments C Laidlaw, B Zhu, S Russell, A Dragan arXiv preprint arXiv:2312.08369 | 6 | 2023 |
Efficient cooperative inverse reinforcement learning M Palaniappan, D Malik, D Hadfield-Menell, A Dragan, S Russell Proc. ICML Workshop on Reliable Machine Learning in the Wild | 6 | 2017 |
Bayesian robustness: A nonasymptotic viewpoint K Bhatia, YA Ma, AD Dragan, PL Bartlett, MI Jordan Journal of the American Statistical Association 119 (546), 1112-1123 | 5 | 2024 |
Scalably solving assistance games C Laidlaw, E Bronstein, T Guo, D Feng, L Berglund, J Svegliato, S Russell, ... ICLR 2025 Workshop on Bidirectional Human-AI Alignment | 5 | 2024 |
Defining deception in decision making M Abdulhai, M Carroll, J Svegliato, A Shrivastava, A Dragan, S Levine | 4 | 2024 |
Context steering: Controllable personalization at inference time JZY He, S Pandey, ML Schrum, A Dragan arXiv preprint arXiv:2405.01768 | 4 | 2024 |
Optimizing robot behavior via comparative language feedback J Tien, Z Yang, M Jun, SJ Russell, A Dragan, E Bıyık Proceedings of the 16th International Conference on Social Robotics (ICSR … | 4 | 2024 |
Contextual reliability: When different features matter in different contexts GR Ghosal, A Setlur, DS Brown, A Dragan, A Raghunathan International Conference on Machine Learning, 11300-11320 | 4 | 2023 |
On the utility of model learning in hri G Swamy, J Schulz, R Choudhury, D Hadfield-Menell, A Dragan arXiv preprint arXiv:1901.01291 | 4 | 2019 |
Temporal Representation Alignment: Successor Features Enable Emergent Compositionality in Robot Instruction Following V Myers, BC Zheng, A Dragan, K Fang, S Levine arXiv preprint arXiv:2502.05454 | 3 | 2025 |
Interactive dialogue agents via reinforcement learning on hindsight regenerations J Hong, J Lin, A Dragan, S Levine arXiv preprint arXiv:2411.05194 | 3 | 2024 |
Efficient Dynamics Estimation With Adaptive Model Sets E Ratner, A Bajcsy, T Fong, CJ Tomlin, AD Dragan IEEE robotics and automation letters 6 (2), 2373-2380 | 3 | 2021 |
Leveraging critical states to develop trust SH Huang, K Bhatia, P Abbeel, AD Dragan RSS 2017 Workshop: Morality and Social Trust in Autonomous Robots | 3 | 2017 |
Pre-school children's first encounter with a robot E Cha, A Dragan, S Srinivasa Proceedings of the 2014 ACM/IEEE international conference on Human-robot … | 3 | 2014 |
Extrinsic calibration from per-sensor egomotion P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 3 | 2013 |
Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation M Pan, M Schrum, V Myers, E Bıyık, A Dragan arXiv preprint arXiv:2406.06714 | 2 | 2024 |
Scalable oversight by accounting for unreliable feedback S Singhal, C Laidlaw, A Dragan ICML 2024 Workshop on Models of Human Feedback for AI Alignment | 2 | 2024 |
Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning J Gao, S Reddy, G Berseth, AD Dragan, S Levine 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems … | 2 | 2023 |
Video-guided skill discovery M Tomar, D Ghosh, V Myers, A Dragan, ME Taylor, P Bachman, S Levine ICML 2023 Workshop The Many Facets of Preference-Based Learning | 2 | 2023 |
Agnostic learning with unknown utilities K Bhatia, PL Bartlett, AD Dragan, J Steinhardt arXiv preprint arXiv:2104.08482 | 2 | 2021 |
Irrationality can help reward inference L Chan, A Critch, A Dragan | 2 | 2019 |
Few-shot intent inference via meta-inverse reinforcement learning K Xu, E Ratner, A Dragan, S Levine, C Finn | 2 | 2018 |
Inferring reward functions from demonstrators with unknown biases R Shah, N Gundotra, P Abbeel, A Dragan | 2 | 2018 |
Assistive teleoperation: A new domain for interactive learning A Dragan, S Srinivasa AAAI fall symposium on robots interactively learning from human teachers, 1-4 | 2 | 2012 |
AssistanceZero: Scalably Solving Assistance Games C Laidlaw, E Bronstein, T Guo, D Feng, L Berglund, J Svegliato, S Russell, ... arXiv preprint arXiv:2504.07091 | 1 | 2025 |
Cos: Enhancing personalization and mitigating bias with context steering S Pandey, JZY He, ML Schrum, A Dragan Neurips Safe Generative AI Workshop 2024 | 1 | 2024 |
Quantifying Assistive Robustness Via the Natural-Adversarial Frontier JZY He, DS Brown, Z Erickson, A Dragan Conference on Robot Learning, 1865-1886 | 1 | 2023 |
Engagement, User Satisfaction, and the Amplification of Divisive Content on Social Media Emilie Flamme S Milli, M Carroll, Y Wang, S Pandey, S Zhao, A Dragan | 1 | 2023 |
Enabling Generalization of Human Models for Human-AI Collaboration to New Tasks X Yang, A Dragan Master’s thesis. EECS Department, University of California, Berkeley. http … | 1 | 2021 |
Xt2: Training an x-to-text typing interface with online learning from implicit feedback J Gao, S Reddy, G Berseth, AD Dragan, S Levine International Conference on Learning Representations (ICLR) | 1 | 2021 |
An extensible interactive interface for agent design M Rahtz, J Fang, AD Dragan, D Hadfield-Menell arXiv preprint arXiv:1906.02641 | 1 | 2019 |
Specifying AI Objectives as a Human-AI Collaboration problem A Dragan Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 329-329 | 1 | 2019 |
Towards Persistent Localization and Mapping with a Continuous Appearance-Based Topology P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 1 | 2013 |
Parsing Indoor Scenes Using RGB-D Imager P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 1 | 2013 |
Recognition, Prediction, and Planning for Assisted Teleoperation of Freeform Tasks P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 1 | 2013 |
Learning to provide better examples for our robots A Dragan, S Srinivasa Carnegie Mellon University | 1 | 2011 |
A Theoretical Explanation of Deep RL Performance in Stochastic Environments C Laidlaw, B Zhu, S Russell, A Dragan NeurIPS 2023 Workshop on Generalization in Planning | 1 | |
The impacts of known and unknown demonstrator irrationality on reward inference L Chan, A Critch, A Dragan | 1 | |
What Would pi* Do?: Imitation Learning via Off-Policy Reinforcement Learning S Reddy, AD Dragan, S Levine | 1 | |
Can AI Mediation Improve Democratic Deliberation? Sébastien A. Krier using Midjourney 6.1 MH Tessler, G Evans, MA Bakker, I Gabriel, S Bridgers, R Jain, R Koster, ... Artificial Intelligence | 2025 | |
Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL J Hong, A Dragan, S Levine arXiv preprint arXiv:2505.18098 | 2025 | |
Achieving AI Alignment with Unreliable Supervision S Singhal, C Laidlaw, A Dragan | 2024 | |
Preventing Reward Hacking with Occupancy Measure Regularization S Singhal, C Laidlaw, A Dragan | 2024 | |
Context Steering: Controllable Personalization at Inference Time J Zhi-Yang He, S Pandey, ML Schrum, A Dragan arXiv e-prints, arXiv: 2405.01768 | 2024 | |
Quantifying Assistive Robustness Via the Natural-Adversarial Frontier J Zhi-Yang He, Z Erickson, DS Brown, AD Dragan arXiv e-prints, arXiv: 2310.10610 | 2023 | |
Collaborative Research: HCC: Medium: Aligning Robot Representations with Humans A Dragan NSF Award Number 2310757. Directorate for Computer and Information Science … | 2023 | |
Similarity-Based Representation Learning Y Liu, A Bobu, A Dragan | 2023 | |
Learning Representations that Enable Generalization in Assistive Tasks J Zhi-Yang He, A Raghunathan, DS Brown, Z Erickson, AD Dragan arXiv e-prints, arXiv: 2212.03175 | 2022 | |
Implicit Communication in Human-Machine Collaboration A Dragan | 2022 | |
Inducing Structure in Reward Learning by Learning A Bobu, M Wiggert, C Tomlin, A Dragan | 2021 | |
Assisted Robust Reward Design J Zhi-Yang He, AD Dragan arXiv e-prints, arXiv: 2111.09884 | 2021 | |
Analyzing Human Models that Adapt Online A Sripathy, A Bobu, D Brown, A Dragan IEEE International Conference on Robotics and Automation | 2021 | |
Explainable Robotic Systems: Introduction to the special issue M DE GRAAF, A DRAGAN, BF MALLE, TOM ZIEMKE | 2021 | |
Project Plan: Benchmarking Representation Learning for Imitation Learning X Chen, S Toyer, C Wild, N Alex, BS Emmons, S Wang, S Russell, ... | 2020 | |
Learning with Humans in the Loop G Swamy, A Dragan, S Levine | 2020 | |
Comparing Game Planners S Luo, A Dragan | 2020 | |
Learning from Intended Corrections JY Zhang, AD Dragan CoRR | 2018 | |
The Off-Switch Game: Incentives for Allowing AI Shutdown D Hadfield-Menell, A Dragan, P Abbeel, S Russell < bound method Organization. get_name_with_acronym of< Organization … | 2017 | |
CAREER: Towards Autonomously Generating Robot Behavior for Coordination with Humans-Accounting for Effects on Human Actions A Dragan NSF Award Number 1652083. Directorate for Computer and Information Science … | 2017 | |
Geometric Mechanics for Continuous Swimmers on Granular Material J Dai, H Faraji, P Schiebel, C Gong, M Travers, R Hatton, D Goldman, ... APS March Meeting Abstracts 2016, V40. 004 | 2016 | |
Publication Submission Form TW Fong, J Scholtz, J Shah, L Flueckiger, C Kunz, D Lees, J Schreiner, ... Journal Article 30 (3), 705-718 | 2014 | |
Legible user input for intent prediction KCT Lee, AD Dragan, SS Srinivasa 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI … | 2013 | |
Distributed Approximation of Joint Measurement Distributions Using Mixtures of Gaussians P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Visual Route Recognition with a Handful of Bits P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Contextual Sequence Prediction with Application to Control Library Optimization P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Failure Anticipation in Pursuit-Evasion P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Real-Time Inverse Dynamics Learning for Musculoskeletal Robots Based on Echo State Gaussian Process Regression P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
What's in the Bag: A Distributed Approach to 3D Shape Duplication with Modular Robots P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
E-Graphs: Bootstrapping Planning with Experience Graphs P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Optimal Control with Weighted Average Costs and Temporal Logic Specifications P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Towards A Swarm of Agile Micro Quadrotors P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Efficiently Finding Optimal Winding-Constrained Loops in the Plane P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Affine Trajectory Deformation for Redundant Manipulators P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Hierarchical Motion Planning in Topological Representations P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Reducing Conservativeness in Safety Guarantees by Learning Disturbances Online: Iterated Guaranteed Safe Online Learning P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Probabilistic Temporal Logic for Motion Planning with Resource Threshold Constraints P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Time-Optimal Trajectory Generation for Path Following with Bounded Acceleration and Velocity P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Nonparametric Bayesian Models for Unsupervised Scene Analysis and Reconstruction P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Minimal Coordinate Formulation of Contact Dynamics in Operational Space P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Inference on Networks of Mixtures for Robust Robot Mapping P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Robust Object Grasping Using Force Compliant Motion Primitives P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
FFT-Based Terrain Segmentation for Underwater Mapping P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Robust Navigation Execution by Planning in Belief Space P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Development of a Testbed for Robotic Neuromuscular Controllers P Agarwal, S Kumar, J Ryde, J Corso, V Krovi, N Ahmed, J Schoenberg, ... MIT Press | 2013 | |
Publication Submission Form TD Niemueller, G Lakemeyer, S Srinivasa, D Berenson, M Cakmak, ... Journal Article 100 (8), 2410-2428 | 2012 | |
The Effective Horizon Challenge C Laidlaw, D Khalil, M Li, L Newhouse, S Russell, A Dragan The Exploration in AI Today Workshop at ICML 2025 | ||
CTRL-Rec: Controlling Recommender Systems With Natural Language M Carroll, A Foote, M Williams, A Dragan, WB Knox, S Milli ICLR 2025 Workshop on Bidirectional Human-AI Alignment | ||
Diagnostic Uncertainty: Teaching Language Models to Describe Open-Ended Uncertainty B Sui, J Lin, M Li, A Dragan, D Klein, J Steinhardt ICLR 2025 Workshop on Building Trust in Language Models and Applications | ||
Zero-Shot Goal Dialogue via Reinforcement Learning on Imagined Conversations J Hong, S Levine, A Dragan | ||
Reliability-Aware Preference Learning for LLM Reward Models S Singhal, C Laidlaw, A Dragan | ||
Targeted Manipulation and Deception Emerge in LLMs Trained on User* Feedback M Williams, M Carroll, C Weisser, B Murphy, A Narang, A Dragan Workshop on Socially Responsible Language Modelling Research | ||
Successor Representations Enable Emergent Compositional Instruction Following V Myers, C Zheng, A Dragan, K Fang, S Levine | ||
CoS: Enhancing Personalization with Context Steering S Pandey, JZY He, ML Schrum, A Dragan Workshop on Socially Responsible Language Modelling Research | ||
Learning human-robot collaboration from human feedback JZY He, A Rai, AD Dragan | ||
RobULA: Efficient Sampling for Robust Bayesian Inference K Bhatia, YA Ma, AD Dragan, MI Jordan, PL Bartlett | ||
Model-Free Shared Autonomy through Deep Human-in-the-Loop Reinforcement Learning S Reddy, A Dragan, S Levine | ||
Publication Submission Form ZAM Marinho, AFT Martins, SB Cohen, NA Smit, A Dragan, A Byravan, ... | ||
Scalable Confidence-Aware Safety Analysis for Robot Planning around Multiple Humans JF Fisac, D Fridovich-Keil, A Bajcsy, S Herbert, S Deglurkar, C Tomlin, ... | ||
Collaborators: Dorsa Sadigh, Chandrayee Basu, Sanjit Seshia A Dragan | ||
Report: Verifiable Control for (Semi) Autonomous Cars that Learns from Human (Re) Actions A Dragan, SS Sastry, SA Seshia | ||
Planning with Observable Operator Models Guided Research Final Report A Dragan | ||
Trajectory Optimization for Predictable and Legible Motion AD Dragan, SS Srinivasa |
* * *
To William Hague, the new Chancellor of Oxford University ~ #OxfordWUaScollaborations ?
general@williamjhague.com - October 2025
| 5:21 PM (1 hour ago) | ![]() ![]() | ||
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@WilliamJHague
·
Nov 27, 2024
It is the greatest honour of my life to have been chosen by my fellow Oxonians to serve as Chancellor of our university.
https://x.com/WilliamJHague/
PPS
William Hague
@WilliamJHague
·
Oct 9
Ten years at number one.
@UniofOxford
has again been ranked the world’s leading university in the
@timeshighered
World University Rankings - a decade of global excellence in research, teaching and innovation.
https://x.com/WilliamJHague/
--
- Scott GK MacLeod
*
https://en.wikipedia.org/wiki/Western_capercaillie
https://commons.wikimedia.org/wiki/Category:Tetrao_urogallus
...
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