Distributed Constraint Optimization (DCOP) is a powerful framework for representing and solving distributed combinatorial problems, where the variables of the problem are owned by different agents. Many multi-agent problems include constraints that produce different gains (or costs) for the participating agents. Asymmetric gains of constrained agents cannot be naturally represented by the standard DCOP model. The present paper proposes a general framework for Asymmetric DCOPs (ADCOPs). In ADCOPs different agents may have different valuations for constraints that they are involved in. The new framework bridges the gap between multi-agent problems which tend to have asymmetric structure and the standard symmetric DCOP model. The benefits of the proposed model over previous attempts to generalize the DCOP model are discussed and evaluated. Innovative algorithms that apply to the special properties of the proposed ADCOP model are presented in detail. These include complete algorithms that have a substantial advantage in terms of runtime and network load over existing algorithms (for standard DCOPs) which use alternative representations. Moreover, standard incomplete algorithms (i.e., local search algorithms) are inapplicable to the existing DCOP representations of asymmetric constraints and when they are applied to the new ADCOP framework they often fail to converge to a local optimum and yield poor results. The local search algorithms proposed in the present paper converge to high quality solutions. The experimental evidence that is presented reveals that the proposed local search algorithms for ADCOPs achieve high quality solutions while preserving a high level of privacy

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Asynchronous Partial Overlay (APO) is a search algorithm that uses cooperative mediation to solve Distributed Constraint Satisfaction Problems (DisCSPs). The algorithm partitions the search into different subproblems of the DisCSP. The original proof of completeness of the APO algorithm is based on the growth of the size of the subproblems. The present paper demonstrates that this expected growth of subproblems does not occur in some situations, leading to a termination problem of the algorithm. The problematic parts in the APO algorithm that interfere with its completeness are identified and necessary modifications to the algorithm that fix these problematic parts are given. The resulting version of the algorithm, Complete Asynchronous Partial Overlay (CompAPO), ensures its completeness. Formal proofs for the soundness and completeness of CompAPO are given. A detailed performance evaluation of CompAPO comparing it to other DisCSP algorithms is presented, along with an extensive experimental evaluation of the algorithm's unique behavior. Additionally, an optimization version of the algorithm, CompOptAPO, is presented, discussed, and evaluated.

Trust and reputation systems for virtual communities are gaining increasing research attention. These systems track members' activities and obtain their reputation to improve the quality of member interactions and reduce the effect of fraudulent members. As virtual communities become a central playground for internet users, the reputation a member gains within a community may be viewed as a social credential. These credentials can serve the user as a means for promoting her status in new communities on one hand, and on the other hand assist virtual communities to broaden their knowledge about users with relatively low activity volume. The Cross-Community Reputation (CCR) model was designed for sharing reputation knowledge across communities. The model identifies the fundamental terms that are required for a meaningful sharing of reputation information between communities and proposes methods to make that information sharing feasible within the boundaries of users' and communities' policies. This paper presents the CR model and draws the architecture guidelines for designing an infrastructure to support it. The proposed model is evaluated by using a sample of real-world users' ratings as well as by conducting a dedicated experiment with real users. The results of the experimental evaluation demonstrate the effectiveness of the CCR model in various aspects.

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