论文信息 - Markov Games as a Framework for Multi-Agent Reinforcement Learning - 字舞流文

Markov Games as a Framework for Multi-Agent Reinforcement Learning

Michael L. Littman | M. Littman

[1] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.

[2] Leon A. Petrosyan,et al. Game Theory (Second Edition) , 1996 .

[3] Ben J. A. Kröse,et al. Learning from delayed rewards , 1995, Robotics Auton. Syst..

[4] Matthias Heger,et al. Consideration of Risk in Reinforcement Learning , 1994, ICML.

[5] Ming Tan,et al. Multi-Agent Reinforcement Learning: Independent versus Cooperative Agents , 1997, ICML.

[6] Holly A. Yanco,et al. An adaptive communication protocol for cooperating mobile robots , 1993 .

[7] Anton Schwartz,et al. A Reinforcement Learning Method for Maximizing Undiscounted Rewards , 1993, ICML.

[8] A. Barto,et al. Learning and Sequential Decision Making , 1989 .

[9] Dimitri P. Bertsekas,et al. Dynamic Programming: Deterministic and Stochastic Models , 1987 .

[10] Jan Telgen,et al. Stochastic Dynamic Programming , 2016 .

[11] R. Howard. Dynamic Programming and Markov Processes , 1960 .

[12] Arthur L. Samuel,et al. Some Studies in Machine Learning Using the Game of Checkers , 1967, IBM J. Res. Dev..

[13] E. Rowland. Theory of Games and Economic Behavior , 1946, Nature.