Achieving cooperation through deep multiagent reinforcement learning in sequential prisoner's dilemmas
Proceedings of the First International Conference on Distributed Artificial Intelligence, pp. 112019.
deep multiagent reinforcement learning mutual cooperation opponent model sequential prisoner's dilemmas
The Iterated Prisoner's Dilemma has guided research on social dilemmas for decades. However, it distinguishes between only two atomic actions: cooperate and defect. In real-world prisoner's dilemmas, these choices are temporally extended and different strategies may correspond to sequences of actions, reflecting grades of cooperation. We ...More
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