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Multi-agent interactions, such as communication, teaching, and bluffing, often rely on higher-order social inference, i.e., understanding how others infer oneself.
Does the chimpanzee have a theory of mind?
Premack, D.; and Woodruff, G. 1978 · 1978
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A framework for sequential planning in multi-agent settings
Gmytrasiewicz, P. J.; and Doshi, P. 2005 · 2005
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Exact solutions of interactive POMDPs using behavioral equivalence
Rathnasabapathy, B.; Doshi, P.; and Gmytrasiewicz, P. 2006 · 2006
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Monte Carlo sampling methods for approximating interactive POMDPs
Doshi, P.; and Gmytrasiewicz, P. J. 2009 · 2009
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Help or hinder: Bayesian models of social goal inference
Ullman, T.; Baker, C.; Macindoe, O.; Evans, O.; Goodman, N.; and Tenenbaum, J. 2009 · 2009
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Predicting pragmatic reasoning in language games
Frank, M. C.; and Goodman, N. D. 2012 · 2012
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Cooperative inverse reinforcement learning
Hadfield-Menell, D.; Russell, S. J.; Abbeel, P.; and Dragan, A. 2016 · 2016
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Neurally-guided procedural models: Amortized inference for procedural graphics programs using neural networks
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Rational quantitative attribution of beliefs, desires and percepts in human mentalizing
Baker, C. L.; Jara-Ettinger, J.; Saxe, R.; and Tenenbaum, J. B. 2017 · 2017
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Le, T. A.; Baydin, A. G.; and Wood, F. 2017 · 2017
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Machine theory of mind
Rabinowitz, N.; Perbet, F.; Song, F.; Zhang, C.; Eslami, S. A.; and Botvinick, M. 2018 · 2018
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Nested reasoning about autonomous agents using probabilistic programs
Seaman, I. R.; van de Meent, J.-W.; and Wingate, D. 2018 · 2018
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Han, Y.; and Gmytrasiewicz, P. 2019 · 2019
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Theory of minds: Understanding behavior in groups through inverse planning
Shum, M.; Kleiman-Weiner, M.; Littman, M. L.; and Tenenbaum, J. B. 2019 · 2019
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Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving
Cao, Z.; Biyik, E.; Wang, W. Z.; Raventos, A.; Gaidon, A.; Rosman, G.; and Sadigh, D. 2020 · 2020
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Using machine theory of mind to learn agent social network structures from observed interactive behaviors with targets
Chuang, Y.-S.; Hung, H.-Y.; Gamborino, E.; Goh, J. O. S.; Huang, T.-R.; Chang, Y.-L.; Yeh, S.-L.; and Fu, L.-C. 2020 · 2020
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Phase: Physically-grounded abstract social events for machine social perception
Netanyahu, A.; Shu, T.; Katz, B.; Barbu, A.; and Tenenbaum, J. B. 2021 · 2021
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Etalumis: Bringing probabilistic programming to scientific simulators at scale
Baydin, A. G.; Shao, L.; Bhimji, W.; Heinrich, L.; Meadows, L.; Liu, J.; Munk, A.; Naderiparizi, S.; Gram-Hansen, B.; Louppe, G.; et al. 2019 · 2019
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Social interactions as recursive mdps
Tejwani, R.; Kuo, Y.-L.; Shu, T.; Katz, B.; and Barbu, A. 2022 · 2022
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