447 citations · 697 across the 26 of their papers we have counts for
3 papers · 2 filters
Human Engagement Providing Evaluative and Informative Advice for Interactive Reinforcement Learning
Adam Bignold, Francisco Cruz, Richard Dazeley +2
Interactive reinforcement learning proposes the use of externally-sourced information in order to speed up the learning process. When interacting with a learner agent, humans may p…
A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review
Adam Bignold, Francisco Cruz, Matthew E. Taylor +4
A long-term goal of reinforcement learning agents is to be able to perform tasks in complex real-world scenarios. The use of external information is one way of scaling agents to mo…
Explainable robotic systems: Understanding goal-driven actions in a reinforcement learning scenario
Francisco Cruz, Richard Dazeley, Peter Vamplew +1
Robotic systems are more present in our society everyday. In human-robot environments, it is crucial that end-users may correctly understand their robotic team-partners, in order t…