Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Artificial Intelligence
The potential for the evolution of co-operation among Web agents
International Journal of Human-Computer Studies - Evolution and learning in multiagent systems
Self-organization through bottom-up coalition formation
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Efficient information gathering on the Internet
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
The effects of kinship bias on multi-agent environments: studies on theoretical models and the internet access problems
Coalition formation among bounded rational agents
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Speciation as automatic categorical modularization
IEEE Transactions on Evolutionary Computation
Adaptive dynamic load-balancing through evolutionary formation of coalitions
Design and application of hybrid intelligent systems
| Hi-index | 0.00 |
Information on the Internet can be collected by autonomous agents that send out queries to the servers that may have the information sought. From a single agent’s perspective, sending out as many queries as possible maximizes the chances of finding the information sought. However, if every agent does the same, the servers will be overloaded. The first major contribution of this paper is proving mathematically that the agents situated in such environments play the n-Person Prisoner’s Dilemma Game. The second is mathematically deriving the notion of effectiveness of cooperation among the agents in such environments and then presenting the optimal interval for the number of information sites for a given number of information-seeking agents. When the optimal interval is satisfied, cooperation among agents is effective, meaning that resources (e.g., servers) are optimally shared. Experimental results suggest that agents can better share available servers through the kinship-based cooperation without explicitly knowing about the entire environment. This paper also identifies difficulties of promoting cooperation in such environments and presents possible solutions. The long-term goal of this research is to elucidate the understanding of massively distributed multiagent environments such as the Internet and to identify valuable design principles of software agents in similar environments.