This paper presents a new look on emergence from the aspect of locality andglobality of evaluation functions for solving traditional computer problems. We first translate theConstraint Satisfaction Problem (CSP) into ...This paper presents a new look on emergence from the aspect of locality andglobality of evaluation functions for solving traditional computer problems. We first translate theConstraint Satisfaction Problem (CSP) into the multi-agent system, and then show how a globalsolution emerges from the system in which every agent uses a local evaluation function to decide itsaction, while comparing to other traditional algorithms, such as Local search and SimulatedAnnealing which use global evaluation functions. We also give some computer experimental results onlarge-scale N-queen problems and κ-Coloring problems, and show that emergence only depends onproblem instance, not details of agent settings, i.e. in some CSPs, the system can self-organize toa global solution, but can not in some other CSPs no matter what settings of agents have.展开更多
基金This paper is supported by the International Program of Santa Fe Institute and the grant of China National Science Foundation(No.70171052).
文摘This paper presents a new look on emergence from the aspect of locality andglobality of evaluation functions for solving traditional computer problems. We first translate theConstraint Satisfaction Problem (CSP) into the multi-agent system, and then show how a globalsolution emerges from the system in which every agent uses a local evaluation function to decide itsaction, while comparing to other traditional algorithms, such as Local search and SimulatedAnnealing which use global evaluation functions. We also give some computer experimental results onlarge-scale N-queen problems and κ-Coloring problems, and show that emergence only depends onproblem instance, not details of agent settings, i.e. in some CSPs, the system can self-organize toa global solution, but can not in some other CSPs no matter what settings of agents have.
