A Genetic Approach to Planning in Heterogeneous Computing Environments

Planning is an artificial intelligence problem with a wide range of real-world applications. Genetic algorithms, neural networks, and simulated annealing are heuristic search methods often used to solve complex optimization problems. In this paper, we propose a genetic approach to planning in the context of workflow management and process coordination on a heterogenous grid. We report results for two planning problems, the Towers of Hanoi and the Sliding-tile puzzle.

• Type: Conference
• Year: 2003
• Where: IPPS
• Authors: Han Yu, Dan C. Marinescu, Annie S. Wu, Howard Jay Siegel
• Keywords: Artificial Intelligence Problem, Complex Optimization Problems, Distributed And Parallel Computing, Heuristic Search Methods, IPPS 2003