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 |