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.

本文通过进化博弈理论和基于代理的建模和仿真技术，对在多智能体系统中通过多个交互者的存在和互动的多种行为策略下涌现和演变的集体行为机制的主要研究方向和挑战进行了总结，包括将认知和情感机制引入智能体的实现、在复杂网络中促进亲社会行为的成本效益干预、AI 安全发展生态的监管和治理以及随机演化多人游戏的平衡分析。总之，本文描述了该小组视图或优先考虑的 MAS 研究中的重要开放问题。

多智能体系统中的演化博弈理论对新兴行为的理解

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

Prosocial behaviors are encountered in the donation game, the prisoner's
dilemma, relaxed social dilemmas, and public goods games. Many studies assume
that the population structure is homogeneous, meaning all individuals have the
same number of interaction partners, or that the social good is of one
particular type. Here, we explore general evolutionary dynamics for arbitrary
spatial structures and social goods. We find that heterogeneous networks,
wherein some individuals have many more interaction partners than others, can
enhance the evolution of prosocial behaviors. However, they often accumulate
most of the benefits in the hands of a few highly-connected individuals, while
many others receive low or negative payoff. Surprisingly, selection can favor
producers of social goods even if the total costs exceed the total benefits. In
summary, heterogeneous structures have the ability to strongly promote the
emergence of prosocial behaviors, but they also create the possibility of
generating large inequality.

研究不同空间结构和社会公共物品在生物进化中如何影响互惠行为，发现异质性网络能够促进互惠行为的出现，但这也可能导致少数人受益，大多数人受益较少或负面影响。此外，研究还发现即使总成本超过总利益，社会产品的制作者也可能受到选择的青睐。