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Joint attention - the ability to purposefully coordinate attention with another agent, and mutually attend to the same thing -- is a critical component of human social cognition.
A longitudinal study of joint attention and language development in autistic children
Mundy, P., Sigman, M., and Kasari, C · 1990
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Joint attention as social cognition
Tomasello, M. et al · 1995
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Long short-term memory
Hochreiter, S. and Schmidhuber, J · 1997
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The dynamics of reinforcement learning in cooperative multiagent systems
Claus, C. and Boutilier, C · 1998
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Imitation and mechanisms of joint attention: A developmental structure for building social skills on a humanoid robot
Scassellati, B · 1998
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Eeg correlates of the development of infant joint attention skills
Mundy, P., Card, J., and Fox, N · 2000
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The emergence of shared attention: Using robots to test developmental theories
Deák, G. O., Fasel, I., and Movellan, J · 2001
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A robot that learns to communicate with human caregivers
Kozima, H. and Yano, H · 2001
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Physical relation and expression: Joint attention for human-robot interaction
Imai, M., Ono, T., and Ishiguro, H · 2003
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A constructive model for the development of joint attention
Nagai, Y., Hosoda, K., Morita, A., and Asada, M · 2003
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A computational model of the emergence of gaze following
Carlson, E. and Triesch, J · 2004
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Intrinsically motivated reinforcement learning
Chentanez, N., Barto, A. G., and Singh, S. P · 2005
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An embodied computational model of social referencing
Thomaz, A. L., Berlin, M., and Breazeal, C · 2005
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A probabilistic model of gaze imitation and shared attention
Hoffman, M. W., Grimes, D. B., Shon, A. P., and Rao, R. P · 2006
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The challenges of joint attention
Kaplan, F. and Hafner, V. V · 2006
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Multi-agent robot systems as distributed autonomous systems
Ota, J · 2006
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Distributed learning and cooperative control for multi-agent systems
Choi, J., Oh, S., and Horowitz, R · 2009
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Towards shared attention through geometric reasoning for human robot interaction
Marin-Urias, L. F., Sisbot, E. A., Pandey, A. K., Tadakuma, R., and Alami, R · 2009
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Joint attention in human-robot interaction
Huang, C.-M · 2010
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Formal theory of creativity, fun, and intrinsic motivation (1990–2010)
Schmidhuber, J · 2010
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Cooperative behavior acquisition in multi-agent reinforcement learning system using attention degree
Kobayashi, K., Kurano, T., Kuremoto, T., and Obayashi, M · 2012
Cited alongside, same era.
Neural machine translation by jointly learning to align and translate
Bahdanau, D., Cho, K., and Bengio, Y · 2014
Cited alongside, same era.
Recurrent models of visual attention
Mnih, V., Heess, N., Graves, A., et al · 2014
Cited alongside, same era.
Safe, multi-agent, reinforcement learning for autonomous driving
Shalev-Shwartz, S., Shammah, S., and Shashua, A · 2016
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Multi-focus attention network for efficient deep reinforcement learning
Choi, J., Lee, B.-J., and Zhang, B.-T · 2017
Cited alongside, same era.
Value-decomposition networks for cooperative multi-agent learning based on team reward
Sunehag, P., Lever, G., Gruslys, A., Czarnecki, W. M., Zambaldi, V. F., Jaderberg, M., Lanctot, M., Sonnerat, N., Leibo, J. Z., Tuyls, K., et al · 2018
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Relational forward models for multi-agent learning
Tacchetti, A., Song, H. F., Mediano, P. A., Zambaldi, V., Rabinowitz, N. C., Graepel, T., Botvinick, M., and Battaglia, P. W · 2018
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Cbam: Convolutional block attention module
Woo, S., Park, J., Lee, J.-Y., and So Kweon, I · 2018
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OpenReview preprint retrieved from https://openreview.net/forum?id=t5lNr0Lw84H , 2018
Yu, C., Velu, A., Vinitsky, E., Wang, Y., Bayen, A., and Wu, Y · 2018
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Attention augmented convolutional networks
Bello, I., Zoph, B., Vaswani, A., Shlens, J., and Le, Q. V · 2019
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Counterfactual multi-agent policy gradients
Foerster, J., Farquhar, G., Afouras, T., Nardelli, N., and Whiteson, S · 2017
Cited alongside, same era.
Cooperative multi-agent control using deep reinforcement learning
Gupta, J. K., Egorov, M., and Kochenderfer, M · 2017
Cited alongside, same era.
Multi-agent reinforcement learning in sequential social dilemmas
Leibo, J. Z., Zambaldi, V., Lanctot, M., Marecki, J., and Graepel, T · 2017
Cited alongside, same era.
Multi-agent actor-critic for mixed cooperative-competitive environments
Lowe, R., Wu, Y. I., Tamar, A., Harb, J., Abbeel, O. P., and Mordatch, I · 2017
Cited alongside, same era.
Learning to maximize return in a stag hunt collaborative scenario through deep reinforcement learning
Nica, A. C., Berariu, T., Gogianu, F., and Florea, A. M · 2017
Cited alongside, same era.
Prosocial learning agents solve generalized stag hunts better than selfish ones
Peysakhovich, A. and Lerer, A · 2017
Cited alongside, same era.
Proximal policy optimization algorithms
Schulman, J., Wolski, F., Dhariwal, P., Radford, A., and Klimov, O · 2017
Cited alongside, same era.
Quantifying generalization in reinforcement learning
Cobbe, K., Klimov, O., Hesse, C., Kim, T., and Schulman, J · 2019
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TF-Agents: A library for reinforcement learning in tensorflow
Guadarrama, S., Korattikara, A., Ramirez, O., Castro, P., Holly, E., Fishman, S., Wang, K., Gonina, E., Wu, N., Kokiopoulou, E., Sbaiz, L., Smith, J., Bartók, G., Berent, J., Harris, C., Vanhoucke, V., and Brevdo, E · 2019
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A survey and critique of multiagent deep reinforcement learning
Hernandez-Leal, P., Kartal, B., and Taylor, M. E · 2019
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Actor-attention-critic for multi-agent reinforcement learning
Iqbal, S. and Sha, F · 2019
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Multi-agent collaborative exploration through graph-based deep reinforcement learning
Luo, T., Subagdja, B., Wang, D., and Tan, A.-H · 2019
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Magnet: Multi-agent graph network for deep multi-agent reinforcement learning
Malysheva, A., Kudenko, D., and Shpilman, A · 2019
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Towards interpretable reinforcement learning using attention augmented agents
Mott, A., Zoran, D., Chrzanowski, M., Wierstra, D., and Rezende, D. J · 2019
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Wang, Z. and Liu, J.-C · 2019
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Multi-agent reinforcement learning: A selective overview of theories and algorithms
Zhang, K., Yang, Z., and Başar, T · 2019
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Learning to solve vehicle routing problems with time windows through joint attention
Falkner, J. K. and Schmidt-Thieme, L · 2020
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Multi-agent game abstraction via graph attention neural network
Liu, Y., Wang, W., Hu, Y., Hao, J., Chen, X., and Gao, Y · 2020
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Learning social learning
Ndousse, K., Eck, D., Levine, S., and Jaques, N · 2020
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Is independent learning all you need in the starcraft multi-agent challenge?
Schroeder de Witt, C., Gupta, T., Makoviichuk, D., Makoviychuk, V., Torr, P. H., Sun, M., and Whiteson, S · 2020
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Neuroevolution of self-interpretable agents
Tang, Y., Nguyen, D., and Ha, D · 2020
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