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The paper presents some aspects of a customable Fuzzy e-Negotiation Agents (FeNAs) system for autonomous multi-issue negotiation in the presence of limited common knowledge and imprecise/soft constraints and preferences. The FeNAs use the principles of utility theory and fuzzy constraint-based reasoning in order to find a consensus that maximizes the agent's utility at the highest possible level of fuzzy constraint satisfaction subject to its acceptability by other agents. A scenario for negotiating document translation services is used to illustrate FeNAs' capabilities for multi-issue integrative negotiation.* The common knowledge can be explicit (e.g. information about private constraints, preferences, utilities etc may be disclosed by fully cooperative agents) or implicit (e.g. agents may have available some information about probability distribution of utilities of other agents).

We propose an improved approach for modeling behaviours of negotiation partners and predictive decision-making based on this modelling. Our prediction is based only on the history of the offers during the current negotiation. The mechanism estimates an influence of different factors contributing to partner's behaviour during negotiation and uses this information to construct a prediction about agent's future behaviour. The optimal sequence of offers is determined according to the prediction. The approach is tested in simple scenarios and the results comparing our approach to random strategy selection are illustrated.

Kowalczyk, R. (2006). A coordinated architecture for the agent-based service level agreement negotiation of web service composition. Australian Software Engineering . USA: IEEE.A coordinated architecture for the agent-based service level agreement negotiation of web service composition AbstractRecent progress in the field of Web services has made it possible to integrate inter-organizational and heterogeneous services on the Web at runtime. If a user request cannot be satisfied by a single Web service, it is (or should be) possible to combine existing services in order to fulfill the request. However, there are several challenging issues that need to be addressed before this can be realized in the true sense. One of them is the ability to ensure end-to-end QoS of a Web service composition. There is a need for a SLA negotiation system which can ensure the autonomous QoS negotiation of Web service compositions irrespective of the application domain. In this paper we propose agent-based coordinated-negotiation architecture to ensure collective functionality, end-to-end QoS and the stateful coordination of complex services. We describe a prototype implementation to demonstrate how this architecture can be used in different application domains. We have also demonstrated how the negotiation system on the service provider's side can be implemented both as an agent based negotiation system and as a Web service based negotiation system. Disciplines Physical Sciences and Mathematics Publication DetailsChhetri, M., Lin, J., Goh, S., Yan, J., Zhang, J. & Kowalczyk, R. (2006

The topic of agent-based service composition has been experiencing much attention recently. Researchers are applying agent technology with the aim to improve adaptiveness and flexibility of prevailing static Web service composition solutions. One major characteristic of multi-agent systems in particular is their ability of emergent behavior that allows gaining complex system behavior from small distributed sets of simple rules. This paper describes a multi-agent-based coalition formation approach for service composition that achieves emergent behavior based on a lightweight interaction protocol and decentralized decision making. The paper also presents evaluation results of first experiments to underline the validity of the approach.

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SUMMARY Cloud Computing is the latest paradigm proposed toward fulfilling the vision of computing being delivered as an utility such as phone, electricity, gas and water services. It enables users to have access to computing infrastructure, platform and software as services over the Internet. The services can be accessed on demand and from anywhere in the world in a quick and flexible manner, and charged for based on their usage, making the rapid and often unpredictable expansion demanded by nowadays' business environment affordable also for small spin‐off and start‐up companies. In order to be competitive, however, Cloud providers need to be able to adapt to the dynamic loads from users, not only optimizing the local usage and costs but also engaging into agreements with other Clouds so as to complement local capacity. The infrastructure in which competing Clouds are able to cooperate to maximize their benefits is called a Federated Cloud. Just as Clouds enable users to cope with unexpected demand loads, a Federated Cloud will enable individual Clouds to cope with unforeseen variations of demand. The definition of the mechanism to ensure mutual benefits for the individual Clouds composing the federation, however, is one of its main challenges. This paper proposes and investigates the application of market‐oriented mechanisms based on the General Equilibrium Theory of Microeconomics to coordinate the sharing of resources between the Clouds in the Federated Cloud. Copyright © 2010 John Wiley & Sons, Ltd.

The paper presents a new approach for multi-agent replanning based on Distributed Constraint Satisfaction (DisCSP) and Graph planning techniques. In this approach, a new distributed refinement strategy is proposed to construct a graph plan for fixing errors occurred during the plan execution. The strategy employs an "max-branching" heuristic that can reduce the final graph plan size and allow faster completion time for the graph construction. The graph plan is then compiled into a DisCSP problem and solved using a multi-variable version of the Asynchronous Backtracking Algorithm. The approach is demonstrated with experiments which show that distributed planning graph and CSP can practically solve the replanning problems in a multi-agent environment.