Do the right thing: studies in limited rationality
Do the right thing: studies in limited rationality
Multiagent diffusion and distributed optimization
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
A framework for distributed problem solving
IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 2
On the Integration of Agent-Based and Mathematical Optimization Techniques
KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
An agent-based framework for solving an equity location problem
KES-AMSTA'11 Proceedings of the 5th KES international conference on Agent and multi-agent systems: technologies and applications
Applications of agent-based models for optimization problems: A literature review
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
Multi-agent System (MAS) can be used to dispose bounded optimization problems with dynamically changing resources because its autonomous distributed management model aspect is fitted to dealing with such external disturbances. One of the problems in multi-agent optimizations is that it is difficult to rigorously define the optimization criteria with respect to the global optimization in advance. Rather, it may depend much on more situated factors such as temporal availability of resources and coexistence of current conflicts, conflicts among what has been already scheduled and what is to be scheduled. In this paper, an organizational model called Garbage Can Model (GCM) is introduced. In GCM, through its three decision-making strategies and the fluidities of problems and resources, solutions made by an individual agent are concerned with several agents that are co-existing in the environment. The problems allocated to each agent are solved not only by an agent's own efforts, but also by the change of problem solving status of other agents. Our simulation experiment shows that GCM is a preferred framework for multi-agent optimization problems in dealing with the above difficulties.