Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...
In this paper we propose a dynamic constraint transformation technique for ensuring timing requirements in a distributed real-time system possessing periodically synchronized dist...
Credit assignment is a fundamental issue for the Learning Classifier Systems literature. We engage in a detailed investigation of credit assignment in one recent system called UC...
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Background: The indexing of scientific literature and content is a relevant and contemporary requirement within life science information systems. Navigating information available ...
Christopher J. O. Baker, Kanagasabai Rajaraman, We...