49 citations · 121 across the 17 of their papers we have counts for
3 papers · 1 filter
Characterizing the Gap Between Actor-Critic and Policy Gradient
Junfeng Wen, Saurabh Kumar, Ramki Gummadi +1
Actor-critic (AC) methods are ubiquitous in reinforcement learning. Although it is understood that AC methods are closely related to policy gradient (PG), their precise connection…
Joint Attention for Multi-Agent Coordination and Social Learning
Dennis Lee, Natasha Jaques, Chase Kew +4
Joint attention - the ability to purposefully coordinate attention with another agent, and mutually attend to the same thing -- is a critical component of human social cognition. I…
Planning and Learning with Stochastic Action Sets
Craig Boutilier, Alon Cohen, Amit Daniely +5
In many practical uses of reinforcement learning (RL) the set of actions available at a given state is a random variable, with realizations governed by an exogenous stochastic proc…