RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
This paper will attempt to explain some of the side-channel attack techniques in a fashion that is easily comprehensible by the layman. What follows is a presentation of three diļ¬...
This paper presents algorithms for the symbolic synthesis of discrete and real-time controllers. At the semantic level the controller is synthesized by nding a winning strategy for...
Optimization in sports is a field of increasing interest. A novel problem in sports management is the Referee Assignment Problem, in which a limited number of referees with differe...
Alexandre R. Duarte, Celso C. Ribeiro, Sebasti&aac...
We consider the deterministic and the randomized decision tree complexities for Boolean functions, denoted DC(f) and RC(f), respectively. A major open problem is how small RC(f) ca...