Achieving cooperation through deep multiagent reinforcement learning in sequential prisoner's dilemmas
Proceedings of the First International Conference on Distributed Artificial Intelligence, pp. 112019.
EI
Keywords:
deep multiagent reinforcement learning mutual cooperation opponent model sequential prisoner's dilemmas
Abstract:
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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