—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
There have been many attempts to study the content of the web, either through human or automatic agents. Five different previously used web survey methodologies are described and ...
Abstract— This paper presents a genetic algorithmic approach for finding efficient paths in directed graphs when optimizing multiple objectives. Its aim is to provide solutions...
Research in collective robotics is motivated mainly by the possibility of achieving an efficient solution to multi-objective navigation tasks when multiple robots are employed, in...
Renato Reder Cazangi, Fernando J. Von Zuben, Maur&...
Answer-set programming (ASP) has emerged recently as a viable programming paradigm well attuned to search problems in AI, constraint satisfaction and combinatorics. Propositional ...