Selection of information types based on personal utility: a testbed for traffic information markets
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Wayward Agents in a Commuting Scenario (Personalities in the Minority Game)
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Congestion tolls as utility alignment between agent and system optimum
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Self-adaptation in a network of social drivers: using random boolean networks
Proceedings of the 2011 workshop on Organic computing
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One of the major research directions in multi-agent systems is dedicated to learning how to coordinate and whether individual agents' decisions can lead to globally optimal or at least acceptable solutions. Our long term goal is to study the effect of several types of information to guide the decision process of the individual agents. This present paper addresses simulation of agents' decision-making regarding route choice, and the role of an information component. This information can be provided by group colleagues, by acquaintances from other groups (small-world), or by route guidance. Besides, we study the role of agents lying about their choices. We compare these scenarios, concluding that information (from some kind of source) is beneficial in general: lying helps only to a certain extent, and route guidance is the best type of information.