Authors:
Matthew Berland
1
and
William Rand
2
Affiliations:
1
Univ. of Texas at Austin, United States
;
2
University of Maryland, United States
Keyword(s):
Participatory simulation, Agent-based model, Agent-based simulation, Complex systems learning.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Simulation
;
Software Engineering
;
Symbolic Systems
;
Web Information Systems and Technologies
;
Web Intelligence
Abstract:
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).