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Found 2 papers, 1 papers with code
A Regularized Opponent Model with Maximum Entropy Objective
In a single-agent setting, reinforcement learning (RL) tasks can be cast into an inference problem by introducing a binary random variable o, which stands for the "optimality".
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Dynamic State Warping
Thus DSW is able to yield alignment that is semantically more interpretable than that of DTW.
