One of the basic issues to face in Multi-Agent Systems is effectively implementingcooperation among agents. To this aim, a not trivial problem has to be solved:Among a (possible large) number of agents, how to detect which agents are promising candidates for cooperation? In this chapter a new approach for dealing with this problem is proposed. We define a formal model for representing agents and a number of semantic properties exploited for detecting fruitful cooperation. On the basis of this model we design a Multi-Agent System, called SPY, capable of managing andsupporting cooperation in the agent community. The system learns semantic propertiesby monitoring the user behavior in such a way that it adapts its response to userexpectation.
Buccafurri, F., Palopoli, L., Rosaci, D., Sarne', G. (2004). Finding the Best Agent for Cooperation. In N. Zhong and J. Liu (a cura di), INTELLIGENT TECHNOLOGIES FOR INFORMATION ANALYSIS (pp. 311-330). DEU : springer [10.1007/978-3-662-07952-2_14].
Finding the Best Agent for Cooperation
SARNE' G
2004
Abstract
One of the basic issues to face in Multi-Agent Systems is effectively implementingcooperation among agents. To this aim, a not trivial problem has to be solved:Among a (possible large) number of agents, how to detect which agents are promising candidates for cooperation? In this chapter a new approach for dealing with this problem is proposed. We define a formal model for representing agents and a number of semantic properties exploited for detecting fruitful cooperation. On the basis of this model we design a Multi-Agent System, called SPY, capable of managing andsupporting cooperation in the agent community. The system learns semantic propertiesby monitoring the user behavior in such a way that it adapts its response to userexpectation.File | Dimensione | Formato | |
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