Enhancing Multi-Agent Based Simulation with Human-Like Decision Making Strategies

Emma Norling, Liz Sonenberg, Ralph Rönnquist

Abstract: We are exploring the enhancement of models of agent behaviour with more “human-like” decision making strategies than are presently available. Our motivation is to build multi-agent based simulations of human societies that would exhibit more realistic simulation behaviours. This in turn will allow researchers to study more complex issues regarding individual and organisational performance than is possible with present systems. Drawing on studies into naturalistic decision making, which looks at people’s decision making in their natural environments, we propose ways of integrating a recognition-primed decision making approach with the popular BDI agent architecture, and report on preliminary empirical studies.