111 citations · 133 across the 2 of their papers we have counts for
3 papers · 1 filter
On the Convergence of Bounded Agents
David Abel, André Barreto, Hado van Hasselt +3
When has an agent converged? Standard models of the reinforcement learning problem give rise to a straightforward definition of convergence: An agent converges when its behavior or…
Near Optimal Behavior via Approximate State Abstraction
David Abel, D. Ellis Hershkowitz, Michael L. Littman
The combinatorial explosion that plagues planning and reinforcement learning (RL) algorithms can be moderated using state abstraction. Prohibitively large task representations can…
Agent-Agnostic Human-in-the-Loop Reinforcement Learning
David Abel, John Salvatier, Andreas Stuhlmüller +1
Providing Reinforcement Learning agents with expert advice can dramatically improve various aspects of learning. Prior work has developed teaching protocols that enable agents to l…