标题： 基于演化博弈论理解多智能体系统中的涌现行为 显示英文标题

标题： Understanding Emergent Behaviours in Multi-Agent Systems with Evolutionary Game Theory

摘要： 多智能体系统（MAS）中集体行为的涌现和演化机制，涉及多个具有不同行为策略的交互代理，在共存条件下，已经通过进化博弈论（EGT）进行了数学研究。 其系统的研究所依赖的方法还包括基于主体建模与仿真（ABM）技术，从而能够在各种条件、参数和替代虚拟游戏中研究上述机制。 本文概述了我们团队使用EGT和ABM方法解决的一些主要研究方向和挑战。 这些研究范围从将认知和情感机制引入演化MAS中的代理实现，到促进复杂网络中亲社会行为的成本高效干预，再到AI安全发展生态的调控与治理，以及随机演化多玩家博弈的平衡分析。 本简报旨在使读者对基于EGT的问题、成果和前景有所了解，这些问题、成果和前景对于机器建模心智及动态MAS中亲社会行为的工程化越来越重要，并且影响着我们对集体行为涌现和稳定性的理解。 在所有情况下，都描述了团队所关注或优先考虑的MAS研究中的重要开放问题。 显示英文摘要

摘要： The mechanisms of emergence and evolution of collective behaviours in dynamical Multi-Agent Systems (MAS) of multiple interacting agents, with diverse behavioral strategies in co-presence, have been undergoing mathematical study via Evolutionary Game Theory (EGT). Their systematic study also resorts to agent-based modelling and simulation (ABM) techniques, thus enabling the study of aforesaid mechanisms under a variety of conditions, parameters, and alternative virtual games. This paper summarises some main research directions and challenges tackled in our group, using methods from EGT and ABM. These range from the introduction of cognitive and emotional mechanisms into agents' implementation in an evolving MAS, to the cost-efficient interference for promoting prosocial behaviours in complex networks, to the regulation and governance of AI safety development ecology, and to the equilibrium analysis of random evolutionary multi-player games. This brief aims to sensitize the reader to EGT based issues, results and prospects, which are accruing in importance for the modeling of minds with machines and the engineering of prosocial behaviours in dynamical MAS, with impact on our understanding of the emergence and stability of collective behaviours. In all cases, important open problems in MAS research as viewed or prioritised by the group are described.