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[1] Tom Schaul,et al. Successor Features for Transfer in Reinforcement Learning , 2016, NIPS.
[2] Sergey Levine,et al. One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning , 2018, Robotics: Science and Systems.
[3] Ramesh Raskar,et al. Designing Neural Network Architectures using Reinforcement Learning , 2016, ICLR.
[4] Yuliy Sannikov. A Continuous-Time Version of the Principal-Agent , 2005 .
[5] Samuel Gershman,et al. Deep Successor Reinforcement Learning , 2016, ArXiv.
[6] Jonathan P. How,et al. Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability , 2017, ICML.
[7] Dan Klein,et al. Modular Multitask Reinforcement Learning with Policy Sketches , 2016, ICML.
[8] Peng Peng,et al. Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat Games , 2017, 1703.10069.
[9] Luciano Messori. The Theory of Incentives I: The Principal-Agent Model , 2013 .
[10] Zeb Kurth-Nelson,et al. Learning to reinforcement learn , 2016, CogSci.
[11] Sarit Kraus,et al. Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination , 2010, AAAI.
[12] Chris L. Baker,et al. Action understanding as inverse planning , 2009, Cognition.
[13] Ryan P. Adams,et al. Gradient-based Hyperparameter Optimization through Reversible Learning , 2015, ICML.
[14] Pieter Abbeel,et al. Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments , 2017, ICLR.
[15] Bart De Schutter,et al. A Comprehensive Survey of Multiagent Reinforcement Learning , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[16] Misha Denil,et al. Learned Optimizers that Scale and Generalize , 2017, ICML.
[17] Sergey Levine,et al. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks , 2017, ICML.
[18] Ali Farhadi,et al. Visual Semantic Planning Using Deep Successor Representations , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[19] Yoshua Bengio,et al. Universal Successor Representations for Transfer Reinforcement Learning , 2018, ICLR.
[20] Bharath Hariharan,et al. Low-Shot Visual Recognition by Shrinking and Hallucinating Features , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[21] David C. Parkes,et al. Policy teaching through reward function learning , 2009, EC '09.
[22] R. Myerson. Optimal coordination mechanisms in generalized principal–agent problems , 1982 .
[23] Paul R. Milgrom,et al. Multitask Principal–Agent Analyses: Incentive Contracts, Asset Ownership, and Job Design , 1991 .
[24] Nikos A. Vlassis,et al. Optimal and Approximate Q-value Functions for Decentralized POMDPs , 2008, J. Artif. Intell. Res..
[25] Michael H. Bowling,et al. Coordination and Adaptation in Impromptu Teams , 2005, AAAI.
[26] Roger B. Myerson,et al. Optimal Auction Design , 1981, Math. Oper. Res..
[27] Anca D. Dragan,et al. Simplifying Reward Design through Divide-and-Conquer , 2018, Robotics: Science and Systems.
[28] Shimon Whiteson,et al. Learning to Communicate with Deep Multi-Agent Reinforcement Learning , 2016, NIPS.
[29] Carlos Guestrin,et al. Multiagent Planning with Factored MDPs , 2001, NIPS.
[30] Daphne Koller,et al. Computing Factored Value Functions for Policies in Structured MDPs , 1999, IJCAI.
[31] Vincent Conitzer,et al. Complexity of Mechanism Design , 2002, UAI.
[32] Shimon Whiteson,et al. QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning , 2018, ICML.
[33] Richard L. Lewis,et al. Reward Design via Online Gradient Ascent , 2010, NIPS.
[34] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[35] Yi Wu,et al. Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments , 2017, NIPS.
[36] David C. Parkes,et al. Value-Based Policy Teaching with Active Indirect Elicitation , 2008, AAAI.
[37] Bengt Holmstrom,et al. Moral Hazard and Observability , 1979 .
[38] H. Francis Song,et al. Machine Theory of Mind , 2018, ICML.
[39] Michael L. Littman,et al. Markov Games as a Framework for Multi-Agent Reinforcement Learning , 1994, ICML.
[40] Marcin Andrychowicz,et al. One-Shot Imitation Learning , 2017, NIPS.
[41] Alex Graves,et al. Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.
[42] Guy Lever,et al. Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward , 2018, AAMAS.