Title :
Collective problem solving through coordinated reaction
Author :
Liu, JyiShane ; Sycara, Katia P.
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
We present a methodology, called Constraint Partition and Coordinated Reaction (CP&CR), for collective, evolutionary problem solving. Problem solving is viewed as an emergent functionality from the evolving process of a group of diverse, interacting, and well-coordinated reactive agents. Cheap and effective search knowledge is extracted from local interactions and embedded in the coordination mechanism. Our domain of problem solving is constraint satisfaction problems. We have applied the methodology to job shop scheduling, an NP-complete constraint satisfaction problem. Experimental results on a benchmark suite of problems show that CP&CR outperformed three other state-of-the-art direct search scheduling techniques, in both efficiency and number of problems solved. In addition, CP&CR was experimentally tested on problems of larger sizes and showed favorable scaling-up characteristics
Keywords :
computational complexity; constraint handling; cooperative systems; problem solving; search problems; Constraint Partition and Coordinated Reaction; NP-complete constraint satisfaction problem; benchmark suite; collective problem solving; constraint satisfaction; coordinated reaction; direct search scheduling; evolutionary problem solving; job shop scheduling; local interactions; scaling-up characteristics; Artificial intelligence; Benchmark testing; Computer science; Job shop scheduling; Partitioning algorithms; Problem-solving; Resource management; Robot kinematics; Search methods;
Conference_Titel :
Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1899-4
DOI :
10.1109/ICEC.1994.349996