Agent Based Model Simulation

This book presents examples of and the latest simulation studies on artificial societies and populations, highlighting innovative implementations of various models of artificial societies and populations using a new, C++-related simulation tool. It demonstrates that the prey-predator models—including spatial distribution, moving patterns, limited renewable food, fear, gregarious (herd) instinct, clustering, epidemics, and competition— are more complex than other publications have suggested, and highlights the great discrepancy between agent-based and conventional continuous models. The book also discusses the modeling and simulation of self-organization and interactions between organizations, including terror organizations, offering fascinating insights into organizational dynamics.

Agent-Based Computer Simulation of Dichotomous Economic Growth reports a project in agent-based computer stimulation of processes of economic growth in a population of boundedly rational learning agents.

This book constitutes the thoroughly refereed post-conference proceedings of the 20th International Workshop on Multi-Agent-Based Simulation, MABS 2020, held in Auckland, New Zealand, in May 2020 collocated with 19th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2020). Due to COVID-19 the workshop has been held online.

This book constitutes the thoroughly refereed post-conference proceedings of the 20th International Workshop on Multi-Agent-Based Simulation, MABS 2020, held in Auckland, New Zealand, in May 2020 collocated with 19th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2020). Due to COVID-19 the workshop has been held online.

Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the “General Reference Model for Agent-based Modeling and Simulation” (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models – from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hardware resources in an optimized fashion.

Simulate Real World Problem, Save Cost, Improve Performance, and Remove Bottlenecks

This collection of excellent papers cultivates a new perspective on agent-based social system sciences, gaming simulation, and their hybridization. Most of the papers included here were presented in the special session titled Agent-Based Modeling Meets Gaming Simulation at ISAGA2003, the 34th annual conference of the International Simulation and Gaming Association (ISAGA) at Kazusa Akademia Park in Kisarazu, Chiba, Japan, August 25–29, 2003.