Predicting interactions between agents in agent-based modeling and simulation of sociotechnical systems

Seung Man Lee, Amy R. Pritchett

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Agent-based modeling and simulation are a valuable research tools for the analysis of dynamic and emergent phenomena of large-scale complex sociotechnical systems. The dynamic behavior of such systems includes both the individual behavior of heterogeneous agents within the system and the emergent behavior arising from interactions between agents; both must be accurately modeled and efficiently executed in simulations. This paper provides a timing and prediction mechanism for the accurate modeling of interactions among agents, correspondingly increasing the computational efficiency of agent-based simulations. A method for assessing the accuracy of interaction prediction methods is described based on signal detection theory. An intelligent interaction timing agent framework that uses a neural network to predict the timing of interactions between heterogeneous agents is presented; this framework dramatically improves the accuracy of interaction timing without requiring detailed scenario-specific modeling efforts for each simulation configuration.

Original languageEnglish (US)
Pages (from-to)1210-1220
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
Volume38
Issue number6
DOIs
StatePublished - Nov 26 2008

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Signal detection
Computational efficiency
Large scale systems
Neural networks

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

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