Intelligent agents designed to work in complex, dynamic environments must respond robustly and flexibly to environmental and circumstantial changes. An agent must be capable of de...
John Thangarajah, James Harland, David N. Morley, ...
To solve real-world discrete optimization problems approximately metaheuristics such as simulated annealing and other local search methods are commonly used. For large instances o...
Abstract. This work presents scale invariant region detectors that apply evolved operators to extract an interest measure. We evaluate operators using their repeatability rate, and...
Abstract. Learning from multi-relational domains has gained increasing attention over the past few years. Inductive logic programming (ILP) systems, which often rely on hill-climbi...
Abstract. The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in...