社会情感主体作为网络囚徒困境中人类行为的模型
Socio-Affective Agents as Models of Human Behaviour in the Networked Prisoner's Dilemma
摘要：
情感控制理论是研究人类情感互动的一个强有力的、普遍的社会学模型。ACT提供了一个经验性的数学模型，作为人类决策的启发式指南。BayesACT是经典ACT的一种变体，它将情感推理与认知（外延或逻辑）推理相结合，就像传统上在AI中发现的那样。贝叶斯ACT允许创建既有情感指导又有目标导向的代理。在这项工作中，我们模拟BayesACT代理在迭代网络囚徒困境（INPD），我们显示四出五个已知的属性，人类发挥INPD复制这些社会情感代理。特别是，我们如何观察到的人类行为的网络结构不变性，反相关的合作和奖励，球员类型分层都清楚的网络贝叶斯ACT代理的紧急属性。我们进一步表明，决策滞后（穆迪条件合作）复制贝叶斯ACT代理在$2/3$的情况下，我们已经考虑。相比之下，以前使用的基于模仿的代理只能复制五个属性中的一个。我们讨论了这些发现在人类代理社会的发展的影响。
英文摘要：
Affect Control Theory (ACT) is a powerful and general sociological model of human affective interaction. ACT provides an empirically derived mathematical model of culturally shared sentiments as heuristic guides for human decision making. BayesACT, a variant on classical ACT, combines affective reasoning with cognitive (denotative or logical) reasoning as is traditionally found in AI. Bayes\-ACT allows for the creation of agents that are both emotionally guided and goal-directed. In this work, we simulate BayesACT agents in the Iterated Networked Prisoner's Dilemma (INPD), and we show four out of five known properties of human play in INPD are replicated by these socio-affective agents. In particular, we show how the observed human behaviours of network structure invariance, anti-correlation of cooperation and reward, and player type stratification are all clearly emergent properties of the networked BayesACT agents. We further show that decision hyteresis (Moody Conditional Cooperation) is replicated by BayesACT agents in over $2/3$ of the cases we have considered. In contrast, previously used imitation-based agents are only able to replicate one of the five properties. We discuss the implications of these findings in the development of human-agent societies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
