The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Migration Policies, Selection Pressure, and Parallel Evolutionary Algorithms
Journal of Heuristics
Test and Evaluation by Genetic Algorithms
IEEE Expert: Intelligent Systems and Their Applications
An analysis of decentralized and spatially distributed genetic algorithms
An analysis of decentralized and spatially distributed genetic algorithms
Simulation for the Social Scientist
Simulation for the Social Scientist
Handbook of Research on Nature-inspired Computing for Economics and Management
Handbook of Research on Nature-inspired Computing for Economics and Management
Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton Studies in Complexity)
Computing with the social fabric: The evolution of social intelligence within a cultural framework
IEEE Computational Intelligence Magazine
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Computational social science in general, and social agent-based modeling (ABM) simulation in particular, are challenged by modeling and analyzing complex adaptive social systems with emergent properties that are hard to understand in terms of components, even when the organization of component agents is know. Evolutionary computation (EC) is a mature field that provides a bio-inspired approach and a suite of techniques that are applicable to and provide new insights on complex adaptive social systems. This paper demonstrates a combined EC-ABM approach illustrated through the RebeLand model of a simple but complete polity system. Results highlight tax rates and frequency of public issue that stress society as significant features in phase transitions between stable and unstable governance regimes. These initial results suggest further applications of EC to ABM in terms of multi-population models with heterogeneous agents, multi-objective optimization, dynamic environments, and evolving executable objects for modeling social change.