Shared memory genetic algorithms in a multi-agent context

In this paper we present a concurrent implementation of genetic algorithms designed for shared memory architectures intended to take advantage of multi-core processor platforms. Our algorithm divides the problems into subproblems as opposed to the usual approach of dividing the population into niches. We show tests for timing and performance on a variety of platforms. Track: Parallel Evolutionary Systems Categories and Subject Descriptors I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence, Multiagent Systems General Terms Algorithms Keywords Parallel genetic algorithms, shared memory, multi-agents

• Type: Conference
• Year: 2010
• Where: GECCO
• Authors: Dana Vrajitoru
• Keywords: Artificial Intelligence, GECCO 2010, Genetic Algorithms, Multi-core Processor Platforms, Optimization