The exchange of goods and services between bargaining software agents requires new forms of brokering mechanisms which achieve consensus between conflicting parties. Such mechanisms have to be designed in a way that they give rational self-interested agents no incentives for insincere behavior. We introduce an arbiter as third party that resolves conflicting bargaining situations between the agents. To achieve non-manipulative agent behavior, we investigate three arbitration protocols that avoid different forms of manipulations and show how each trades net efficiency for robustness against manipulations. We describe the applicability of the protocols in bilateral bargaining situations and, analyze their robustness against manipulations analytically and by simulations. We compare the protocols with Nash's arbitration1 and the Groves-Clarke tax2 and characterize situations in which our protocols are superior.
Softwareagents, artificial intelligent "representatives" of the interests of supply chain participants, enhance the effectiveness and efficiency of Business-to-Business (B2B) e-commerce systems that support modern supply chains. The interorganizational transaction flow starts with a matchmaking process in which suppliers' agents are matched with demanders' agents. The matched agents then negotiate either directly or with the aid of an arbiter. The deal agreed to by the negotiating agents is then executed. The matchmaking and arbitration processes support the achievement of transactions that benefits both sides over many repeated transactions. Matchmaking pairs agents with the least conflicting interests, and arbitration seeks consensus between the negotiating parties within reasonable time and costs while discouraging insincere behavior by the participants. Both processes require a trusted, honest intermediary to achieve appropriate matchmaking and arbiter consensus among all the parties. In this paper we analyze matchmaking in a stable two-sided market, where each seller is matched with a single buyer, and all agents on both sides are matched. We discuss matchmaking in conjunction with arbitration protocols, and analyze their performance through simulation.
Mobile computing and workgroup computing are emerging technologies which have so far been treated independently. Current approaches to support cooperative work neglect the special characteristics of mobile environments like limited bandwidth or temporary disconnection. On the other hand, approaches to support disconnected operation rely on the assumption that the degree of data-sharing is low which is obviously not appropriate for cooperative work. In this paper, we utilize the COACT cooperative transaction model to provide support for parallel activities in mobile environments. We present a system architecture that is able to cope with the special characteristics of mobile environments and a formal framework for the consistent information exchange between mobile users. The paper shows how the COACT history merge algorithm reduces conflicts by exploiting operation semantics and offering consistent sequences of operations. We believe that our new approach is a viable solution to the growing demand for cooperation in mobile environments.
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