Effects of interaction topology and activation regime in several mutli-agent systems
MABS 2000 Proceedings of the second international workshop on Multi-agent based simulation
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Theory of Modeling and Simulation
Theory of Modeling and Simulation
Dynamics of a class of ants on a one-dimensional lattice
Theoretical Computer Science - Discrete applied problems, florilegium for E. Goles
Coordinating change of agents' states in situated agents models
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Modeling dynamic environments in multi-agent simulation
Autonomous Agents and Multi-Agent Systems
The IRM4S model: the influence/reaction principle for multiagent based simulation
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
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It is to date an open question to know how the updating methods affect the evolution of a multi-agent system. This question has been tackled for various complex systems such as cellular automata, Boolean networks, neural networks but little is known for multi-agent systems, especially for the models with a complex behaviour which emerges from simple local rules. This paper focuses on a multi-turmite model, namely the multiple Langton's ants model. All the agents are updated simultaneously and the variation of the updating scheme consists only in choosing different strategies for solving the conflicts produced when two or more agents want to go on the same location. We show that for the same formulation of the agents' behaviour, and the same initial conditions, the use of different updating schemes may lead to qualitatively different evolutions of the system. As a positive spin-off of this study, we exhibit new phenomena of the multi-turmite model such as deadlocks or gliders.