Artificial Intelligence - Special issue on knowledge representation
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Self-Organizing Maps
The Distributed Constraint Satisfaction Problem: Formalization and Algorithms
IEEE Transactions on Knowledge and Data Engineering
A MAX-MIN Ant System for the University Course Timetabling Problem
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
The AMAS theory for complex problem solving based on self-organizing cooperative agents
WETICE '03 Proceedings of the Twelfth International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises
Minimal perturbation problem in course timetabling
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
Interactively solving school timetabling problems using extensions of constraint programming
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
A Goal-Oriented Approach for Modelling Self-organising MAS
ESAW '09 Proceedings of the 10th International Workshop on Engineering Societies in the Agents World X
Processes engineering and AOSE
AOSE'10 Proceedings of the 10th international conference on Agent-oriented software engineering
Techniques for multi-agent system reorganization
ESAW'05 Proceedings of the 6th international conference on Engineering Societies in the Agents World
Hi-index | 0.00 |
This paper presents the usage of cooperative self-organization to design adaptive artificial systems. Cooperation can be viewed as a local criterion for agents to self-organize and then to perform a more adequate collective function. This paper shows an application of cooperative behaviors to a dynamic distributed timetabling problem, ETTO, in which the constraint satisfaction is distributed among cooperative agents. This application has been prototyped and shows positive results on adaptation, robustness and efficiency of this kind of approach.