What does RL stand for?

Topics discussed include representing case variations for learning general and specific adaptation rules, a theorem prover with dependent types of reasoning about actions, probabilistic association rules for item-based recommender systems, semantics for containment belief revision in the case of consistent complete theories, integrating individual and social intelligence into module-based agents without a central coordinator, improving batch reinforcement learning performance through transfer of samples, managing risk in recurrent auctions for robust resource allocation, and domain-dependent view of multiple robots path planning.

Written for students and researchers in social computing, artificial intelligence and cognitive informatics, this volume covers topics such as promoting pro-social behavior through virtual learning environments, proxy agents using reinforcement learning and social transmission through partner selection.

In this case, the reinforcement learning (RL) shows its particular superiority, which just needs very simple information such as estimable and critical information, "right" or "wrong" [3].

We are least aware of our primitive reinforcement learning system located in the basal ganglia.

Abstract: Most reinforcement learning approaches consider Markov decision processes (MDPs) with a single criterion.

Reinforcement learning is a synonym of learning by interaction.

is a reinforcement learning tool assisting instructors that provides user and instructor with intrinsic feedback consisting of information about user's performance.

Reinforcement learning is related to multiarmed bandit problems, and is based on two principles.