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Agent-based modeling: a revolution?

Steven C Bankes1

  • 1RAND, 1700 Main Street, Santa Monica, CA 90407, USA. bankes@rand.org

Proceedings of the National Academy of Sciences of the United States of America
|May 9, 2002
PubMed
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Agent-based modeling (ABM) shows revolutionary potential for social science research. However, realizing this potential requires addressing key challenges identified in recent studies.

Area of Science:

  • Social Science
  • Computational Social Science
  • Complex Systems

Background:

  • Agent-based modeling (ABM) is increasingly recognized for its transformative potential in social sciences.
  • Current applications demonstrate promise, but widespread impact is yet to be fully realized.

Purpose of the Study:

  • To synthesize the challenges hindering the full realization of agent-based modeling's revolutionary potential in social science.
  • To survey the critical issues identified across a session of related papers.

Main Methods:

  • Review and synthesis of papers presented in a specific colloquium session.
  • Identification and categorization of recurring challenges in agent-based modeling implementation and adoption.

Main Results:

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  • A consensus exists that agent-based modeling offers revolutionary prospects for social science.
  • The primary obstacles lie in bridging the gap between ABM's potential and its current demonstrated results.
  • Several key challenges must be overcome for the anticipated revolution to materialize.

Conclusions:

  • Agent-based modeling is poised to revolutionize social science, but significant hurdles remain.
  • Addressing these identified challenges is crucial for unlocking the full potential of ABM in empirical social science research.