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Multi-objective agent-based modeling/Evidence
Method evidence record

Multi-objective agent-based modeling

Multi-Objective Agent-Based Modeling (MO-ABM) couples agent-based simulation with multi-objective optimization to simultaneously optimize several conflicting performance criteria across complex adaptive systems. Autonomous agents interact according to behavioral rules while an optimizer searches for parameter configurations that achieve Pareto-optimal trade-offs among competing system-level goals.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Multi-Objective Agent-Based Modeling
Taxonomic method record · process-pipeline / simulation
  • Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Chichester. · ISBN 9780471873396
  • Tesfatsion, L., Judd, K. L. (Eds.) (2006). Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics. North-Holland, Amsterdam. · ISBN 9780444512536
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyAgent-Based Modelingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-objective genetic algorithmmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-Objective Optimizationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-objective system dynamicsmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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