An investigation into distributed constraint-directed factory scheduling
Proceedings of the sixth conference on Artificial intelligence applications
An overview of distributed artificial intelligence
Foundations of distributed artificial intelligence
Belief-desire-intention agent architectures
Foundations of distributed artificial intelligence
Negotiation and cooperation in multi-agent environments
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Conjectural Equilibrium in Multiagent Learning
Machine Learning
Cooperative Multiagent Systems: A Personal View of the State of the Art
IEEE Transactions on Knowledge and Data Engineering
Multi-agent learning for adaptive scheduling
Multi-agent learning for adaptive scheduling
Utilization and fairness in spectrum assignment for opportunistic spectrum access
Mobile Networks and Applications
The theory and experiments of designing cooperative intelligent systems
Decision Support Systems
Cooperation in competition: efficiently representing and reasoning about coalitional games
Cooperation in competition: efficiently representing and reasoning about coalitional games
e-Work based collaborative optimization approach for strategic logistic network design problem
Computers and Industrial Engineering
A collaborative sensor network middleware for automated production systems
Computers and Industrial Engineering
Computers and Industrial Engineering
Distributed energy balanced routing for wireless sensor networks
Computers and Industrial Engineering
Approximate strong equilibrium in job scheduling games
Journal of Artificial Intelligence Research
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Agent-based game-theoretic model for collaborative web services: Decision making analysis
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
We consider game-theoretic principles for design of cooperative and competitive (non-cooperative self-interested) multi-agent systems. Using economic concepts of tatonnement and economic core, we show that cooperative multi-agent systems should be designed in games with dominant strategies that may lead to social dilemmas. Non-cooperative multi-agent systems, on the other hand, should be designed for games with no clear dominant strategies and high degree of problem complexity. Further, for non-cooperative multi-agent systems, the number of learning agents should be carefully managed so that solutions in the economic core can be obtained. We provide experimental results for the design of cooperative and non-cooperative MAS from telecommunication and manufacturing industries.