Dynamic structures in modeling and simulation: a reflective approach
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Adaptive algorithms for the dynamic distribution and parallel execution of agent-based models
Journal of Parallel and Distributed Computing - Special issue on parallel bioinspired algorithms
A hybrid agent-cellular space modeling approach for fire spread and suppression simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Modeling dynamic environments in multi-agent simulation
Autonomous Agents and Multi-Agent Systems
Modeling agents and their environment
AOSE'02 Proceedings of the 3rd international conference on Agent-oriented software engineering III
Environments for multiagent systems state-of-the-art and research challenges
E4MAS'04 Proceedings of the First international conference on Environments for Multi-Agent Systems
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
CARE@AI'09/CARE@IAT'10 Proceedings of the CARE@AI 2009 and CARE@IAT 2010 international conference on Collaborative agents - research and development
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Multi-agent simulations gain more and more importance for the simulation of complex systems. In order to meet the continuously increasing requirements regarding complexity, level of detail, and size of the model on the one hand and an efficient modeling and execution on the other hand, a reasonable theoretical foundation is essential. Based on the awareness that at the current time these foundations of multi-agent simulation are weak in comparison to other simulation paradigms, the necessity for a general approach for defining and describing a multi-agent simulation is examined. Following this investigation, an exemplary reference model for agent-based modeling and simulation is introduced. This reference model is intended to provide a common understanding of agent-based models along with well-defined semantics of their simulation. In addition, it permits the implementation of various simulators adhering to the specified semantics using the same model and producing identical simulation runs.