標題: Using self-aware agents to analyze public self-consciousness in the iterated prisoner's dilemma
作者: Huang, Chung-Yuan
Wang, Sheng-Wen
Sun, Chuen-Tsai
資訊工程學系
Department of Computer Science
關鍵字: self-aware agents;public self-consciousness;cellular automata;small-world networks;tit-for-tat strategy;win-stay;lose-shift strategy
公開日期: 1-七月-2011
摘要: Self-aware individuals are more likely to consider whether their actions are appropriate in terms of public self-consciousness, and to use that information to execute behaviors that match external standards and/or expectations. The learning concepts through which individuals monitor themselves have generally been overlooked by artificial intelligence researchers. Here we report on our attempt to integrate a self-awareness mechanism into an agent's learning architecture. Specifically, we describe (a) our proposal for a self-aware agent model that includes an external learning mechanism and internal cognitive capacity with super-ego and ego characteristics; and (b) our application of a version of the iterated prisoner's dilemma representing conflicts between the public good and private interests to analyze the effects of self-awareness on an agent's individual performance and cooperative behavior. Our results indicate that self-aware agents who consider public self-consciousness utilize rational analysis in a manner that promotes cooperative behavior and supports faster societal movement toward stability. We found that a small number of self-aware agents are sufficient for improving social benefits and resolving problems associated with collective irrational behaviors.
URI: http://dx.doi.org/10.1177/0037549710391822
http://hdl.handle.net/11536/22330
ISSN: 0037-5497
DOI: 10.1177/0037549710391822
期刊: SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL
Volume: 87
Issue: 7
起始頁: 600
結束頁: 615
顯示於類別:期刊論文


文件中的檔案:

  1. 000290905900003.pdf