Artificial life focuses on synthesizing “life-like behaviors from scratch in computers, machines, molecules, and other alternative media” [24]. Artificial life expands the “horizons of empirical research in biology beyond the territory currently circumscribed by life-as-we-know-it” to provide “access to the domain of life-as-it-could-be” [24]. Agent-based modeling and simulation (ABMS) are used to create computational laboratories that replicate real or potential behaviors of actual or possible complex adaptive systems (CAS). The goal of agent modeling is to allow experimentation with simulated complex systems. To achieve this, agent-based modeling uses sets of agents and frameworks for simulating the agent's decisions and interactions. Agent models show how complex adaptive systems may evolve through time in a way that is difficult to predict from knowledge of the behaviors of the individual agents alone. Agent-based modeling thus provides a natural framework in which to perform artificial life experiments. The free and open source Recursive Porous Agent Simulation Toolkit (Repast) family of tools consists of several advanced agent-based modeling toolkits.
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North, M.J., Macal, C.M. (2009). Foundations of and Recent Advances in Artificial Life Modeling with Repast 3 and Repast Simphony. In: Komosinski, M., Adamatzky, A. (eds) Artificial Life Models in Software. Springer, London. https://doi.org/10.1007/978-1-84882-285-6_2
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