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The ability to model the mental states of others is crucial to human social intelligence, and can offer similar benefits to artificial agents with respect to the social dynamics induced in multi-agent settings.
Does the chimpanzee have a theory of mind?
Premack, D. and Woodruff, G · 1978
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The belief-desire-intention model of agency
Georgeff, M., Pell, B., Pollack, M., Tambe, M., and Wooldridge, M · 1999
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The development of theory of mind in early childhood
Astington, J. W. and Edward, M. J · 2010
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The development of mentalisation in children from a theory of mind perspective
Ensink, K. and Mayes, L. C · 2010
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Bayesian theory of mind: Modeling joint belief-desire attribution
Baker, C., Saxe, R., and Tenenbaum, J · 2011
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Variational information maximisation for intrinsically motivated reinforcement learning
Mohamed, S. and Jimenez Rezende, D · 2015
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Opponent modeling in deep reinforcement learning
He, H., Boyd-Graber, J., Kwok, K., and Daumé III, H · 2016
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Multi-agent actor-critic for mixed cooperative-competitive environments
Lowe, R., Wu, Y., Tamar, A., Harb, J., Abbeel, P., and Mordatch, I · 2017
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Curiosity-driven exploration by self-supervised prediction
Pathak, D., Agrawal, P., Efros, A. A., and Darrell, T · 2017
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Proximal policy optimization algorithms
Schulman, J., Wolski, F., Dhariwal, P., Radford, A., and Klimov, O · 2017
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Intent-aware multi-agent reinforcement learning
Qi, S. and Zhu, S.-C · 2018
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Machine theory of mind
Rabinowitz, N., Perbet, F., Song, F., Zhang, C., Eslami, S. A., and Botvinick, M · 2018
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Neural-symbolic vqa: Disentangling reasoning from vision and language understanding
Yi, K., Wu, J., Gan, C., Torralba, A., Kohli, P., and Tenenbaum, J · 2018
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Social influence as intrinsic motivation for multi-agent deep reinforcement learning
Jaques, N., Lazaridou, A., Hughes, E., Gulcehre, C., Ortega, P., Strouse, D., Leibo, J. Z., and De Freitas, N · 2019
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Theory of mind as inverse reinforcement learning
Jara-Ettinger, J · 2019
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Probabilistic recursive reasoning for multi-agent reinforcement learning
Wen, Y., Yang, Y., Luo, R., Wang, J., and Pan, W · 2019
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Learning a prior over intent via meta-inverse reinforcement learning
Xu, K., Ratner, E., Dragan, A., Levine, S., and Finn, C · 2019
A brain-inspired model of theory of mind
Zeng, Y., Zhao, Y., Zhang, T., Zhao, D., Zhao, F., and Lu, E · 2020
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Theory of mind for deep reinforcement learning in hanabi
Fuchs, A., Walton, M., Chadwick, T., and Lange, D · 2021
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Deep interpretable models of theory of mind
Oguntola, I., Hughes, D., and Sycara, K · 2021
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Learning human rewards by inferring their latent intelligence levels in multi-agent games: A theory-of-mind approach with application to driving data
Tian, R., Tomizuka, M., and Sun, L · 2021
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Symmetric machine theory of mind
Sclar, M., Neubig, G., and Bisk, Y · 2022
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Tom2c: Target-oriented multi-agent communication and cooperation with theory of mind
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Post-hoc concept bottleneck models
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Mind the gap: Challenges of deep learning approaches to theory of mind
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Multiagent inverse reinforcement learning via theory of mind reasoning
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