Genetic Algorithms are very powerful search methods that are used in different optimization problems. Parallel versions of genetic algorithms are easily implemented and usually in...
In this paper, we study the simultaneousdriver and wire sizing (SDWS) problem under two objective functions: (i) delay minimization only, or (ii) combined delay and power dissipat...
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Previous research into the efficiency of text retrieval systems has dealt primarily with methods that consider inverted lists in sequence; these methods are known as term-at-a-tim...
Distributed problem solving by a multiagent system represents a promising approach to solving complex computational problems. However, many multiagent systems require certain degr...