Many researchers have used text classification method in solving the ontology mapping problem. Their mapping results heavily depend on the availability of quality exemplars used as...
Importance sampling-based algorithms are a popular alternative when Bayesian network models are too large or too complex for exact algorithms. However, importance sampling is sensi...
Abstract. Variables and constraints in problem domains are often distributed. These distributed constraint satisfaction problems (DCSPs) lend themselves to multiagent solutions. Mo...
The evaluation or fitness function is a key component of any heuristic search algorithm. This paper introduces a new evaluation function for the well-known graph K-coloring proble...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
This paper focuses on the design of control strategies for Evolutionary Algorithms. We propose a method to encapsulate multiple parameters, reducing control to only one criterion. ...
Abstract. We aim to construct an automatic system for the discovery of collision-based universal cellular automata that simulate Turing machines in their space-time dynamics using ...
We present GP-HH, a framework for evolving local-search 3-SAT heuristics based on GP. The aim is to obtain “disposable” heuristics which are evolved and used for a specific su...
The work presented in this paper is part of the development of a robotic system able to learn context dependent visual clues to navigate in its environment. We focus on the obstacl...