Achieving cooperation through deep multiagent reinforcement learning in sequential prisoner's dilemmas

Proceedings of the First International Conference on Distributed Artificial Intelligence, pp. 112019.

Cited by: 14|Bibtex|Views41|Links
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

Code:

Data:

Your rating :
0

 

Tags
Comments