A simulation approach based on negotiation and cooperation between agents: a case study

Presents AGENDA (A GENeral testbed for Distributed AI Applications), a simulation tool developed for the simulation and design of applications involving interacting entities. This testbed consists of two different levels, the architecture level and the system development level. The architecture level describes a methodology for designing software agents by providing several important functionalities an agent should have. On the other hand, the system development level provides the basic knowledge representation formalism, general inference mechanisms, and a simulation tool-box supporting visualization and monitoring of agents. Following this, the applicability of AGENDA to the transportation domain is presented in detail. The main challenge of AGENDA in the context of this domain has been to provide different cooperation-scalable methods based on negotiation, leading to different scheduling mechanisms, and to experimentally evaluate these mechanisms. This evaluation shows that: (1) AGENDA is suitable for realistic application in the transportation domain; (2) the mechanisms used for vertical negotiation (between trucks considered as agents) and for horizontal negotiation (between companies considered as agents) are applicable for the real-world transportation domain applications. Finally, a complete study of the scalability of the simulation tool and the algorithms used for the negotiation is presented. This study, along with the evaluation of the different mechanisms, can help designers of transportation companies, particularly in the case of large companies