26 citations · 46 across the 3 of their papers we have counts for
4 papers
Broad-persistent Advice for Interactive Reinforcement Learning Scenarios
Francisco Cruz, Adam Bignold, Hung Son Nguyen +2
The use of interactive advice in reinforcement learning scenarios allows for speeding up the learning process for autonomous agents. Current interactive reinforcement learning rese…
Persistent Rule-based Interactive Reinforcement Learning
Adam Bignold, Francisco Cruz, Richard Dazeley +2
Interactive reinforcement learning has allowed speeding up the learning process in autonomous agents by including a human trainer providing extra information to the agent in real-t…
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…