Dynamic BPR using a task/communication model
ACM SIGGROUP Bulletin
Modeling Task and Teams through Game Theoretical Agents
FAABS '00 Proceedings of the First International Workshop on Formal Approaches to Agent-Based Systems-Revised Papers
An evolutionary game-theoretic approach to congestion control
Performance Evaluation - Performance 2005
| Hi-index | 0.00 |
Congestion control in MAS is addressed through a network of agents communicating with each other, for issuing and responding to assistance requests. The network state is analyzed as a particular qualitative game, called Game of Deterrence. A congestion avoidance algorithm is proposed, on the basis of the game solutions. The relation between the type of game reflecting the structure of the agent network, and the occurrence of congestion is then analyzed, highlighting the impact of the network size, and leading to the alternative of either implementing the algorithm, or breaking down the global network in regional networks inside which the congestion occurrence probability is low. The method is then extended to the dynamic case through an example showing existence of cycles.