Participatory simulation, as described by Wilensky & Stroup (1999c), is a form of agent-based simulation in which multiple humans control or design individual agents in the simulation. For instance, in a participatory simulation of an ecosystem, fifty participants might each control the intake and output of one agent, such that the food web emerges from the interactions of the human-controlled agents. We argue that participatory simulation has been under-utilized outside of strictly educational contexts, and that it provides myriad benefits to designers of traditional agent-based simulations. These benefits include increased robustness of the model, increased comprehensibility of the findings, and simpler design of individual agent behaviors. To make this argument, we look to recent research such as that from crowdsourcing (von Ahn, 2005) and the reinforcement learning of autonomous agent behavior (Abbeel, 2008).
ICAART 2009: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE
Participatory simulation,Agent-based model,Agent-based simulation,Complex systems learning
Autonomous agent,Intelligent agent,Computer science,Agent-based social simulation,Crowdsourcing,Knowledge management,Robustness (computer science),Participatory simulation,Reinforcement learning