Utility-Based Mechanism for Structural Self-Organization in Service-Oriented MAS

Structural relations established among agents influence the performance of decentralized service discovery process in multiagent systems. Moreover, distributed systems should be able to adapt their structural relations to changes in environmental conditions. In this article, we present a service-oriented multiagent systems, where agents initially self-organize their structural relations based on the similarity of their services. During the service discovery process, agents integrate a mechanism that facilitates the self-organization of their structural relations to adapt the structure of the system to the service demand. This mechanism facilitates the task of decentralized service discovery and improves its performance. Each agent has local knowledge about its direct neighbors and the queries received during discovery processes. With this information, an agent is able to analyze its structural relations and decide when it is more appropriate to modify its direct neighbors and select the most suitable acquaintances to replace them. The experimental evaluation shows how this self-organization mechanism improves the overall performance of the service discovery process in the system when the service demand changesThis work is partially supported by the Spanish Ministry of Science and Innovation through grants CSD2007-0022 (CONSOLIDER-INGENIO 2010), TIN2012-36586-C03-01, TIN2012-36586-C03-01, TIN2012-36586-C03-02, PROMETEOII/2013/019, and FPU grant AP-2008-00601 awarded to E. Del Val.Del Val Noguera, E.; Rebollo Pedruelo, M.; Vasirani, M.; Fernández, A. (2014). Utility-Based Mechanism for Structural Self-Organization in Service-Oriented MAS. ACM Transactions on Autonomous and Adaptive Systems. 9(3):1-24. https://doi.org/10.1145/2651423S12493Sherief Abdallah and Victor Lesser. 2007. 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Strategies for cooperation emergence in distributed service discovery

This is an Accepted Manuscript of an article published by Taylor & Francis in Cybernetics and Systems on APR 3 2014], available online:http://www.tandfonline.com/10.1080/01969722.2014.894848[EN] In distributed environments where entities only have a partial view of the system, cooperation plays a key issue. In the case of decentralized service discovery in open agent societies, agents only know about the services they provide and who are their direct neighbors. Therefore, they need the cooperation of their neighbors in order to locate the required services. However, cooperation is not always present in open systems. Non-cooperative agents pursuing their own goals could refuse to forward queries from other agents to avoid the cost of this action; therefore, the efficiency of the decentralized service discovery could be seriously damaged. In this paper, we propose the ombination of incentives and local structural changes in order to promote cooperation in the service discovery process. The results show that, even in scenarios where the predominant behavior is not collaborative cooperation emerges.The work was partially supported by the Spanish Ministry of Science and Innovation through grants TIN2009-13839-C03-01, TIN2012-36586-C03-01, CSD2007-0022 (CONSOLIDER-INGENIO 2010).Del Val Noguera, E.; Rebollo Pedruelo, M.; Botti, V. (2014). Strategies for cooperation emergence in distributed service discovery. Cybernetics and Systems. 45(3):220-240. https://doi.org/10.1080/01969722.2014.894848S220240453Blanc , A. , Y.K. Liu , and A. Vahdat . “Designing Incentives for Peer-to-Peer Routing.” InProceedings of the 24th Annual Joint Conference of the IEEE Computer and Communications Societies, Vol. 1, pp. 374–385, 2005 .del Val , E. “Semantic Service Management in Service-Oriented Multi-Agent Systems.” Ph.D. thesis, Departament de Sistemes Informàtics i Computació, Universitat Politècnica de València, 2013 .Del Val, E., Rebollo, M., & Botti, V. (2012). 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Recognition and reward system for peer-reviewers

Peer reviewing plays an important role in the academic publishing process that scrutinizes and provides feedback on the scientific work prior to publication. Peer-reviewers put their efforts in reviewing others research work voluntarily, without any expectations of incentives or rewards. The peer-review process has been criticized for its defects like slowness, bias and abuse of the process. In this paper, we present a model to address these issues by using the approach of recording peer-review data on the blockchain. By using the semantic web and linked data technologies, this system would be able to expose its data and interact with other systems. This system will be used to quantify, recognize and incentivize the peer-reviewing efforts by researchers

Transaction Propagation on Permissionless Blockchains: Incentive and Routing Mechanisms

Existing permissionless blockchain solutions rely on peer-to-peer propagation mechanisms, where nodes in a network transfer transaction they received to their neighbors. Unfortunately, there is no explicit incentive for such transaction propagation. Therefore, existing propagation mechanisms will not be sustainable in a fully decentralized blockchain with rational nodes. In this work, we formally define the problem of incentivizing nodes for transaction propagation. We propose an incentive mechanism where each node involved in the propagation of a transaction receives a share of the transaction fee. We also show that our proposal is Sybil-proof. Furthermore, we combine the incentive mechanism with smart routing to reduce the communication and storage costs at the same time. The proposed routing mechanism reduces the redundant transaction propagation from the size of the network to a factor of average shortest path length. The routing mechanism is built upon a specific type of consensus protocol where the round leader who creates the transaction block is known in advance. Note that our routing mechanism is a generic one and can be adopted independently from the incentive mechanism.Comment: 2018 Crypto Valley Conference on Blockchain Technolog

The PeerRank Method for Peer Assessment

We propose the PeerRank method for peer assessment. This constructs a grade for an agent based on the grades proposed by the agents evaluating the agent. Since the grade of an agent is a measure of their ability to grade correctly, the PeerRank method weights grades by the grades of the grading agent. The PeerRank method also provides an incentive for agents to grade correctly. As the grades of an agent depend on the grades of the grading agents, and as these grades themselves depend on the grades of other agents, we define the PeerRank method by a fixed point equation similar to the PageRank method for ranking web-pages. We identify some formal properties of the PeerRank method (for example, it satisfies axioms of unanimity, no dummy, no discrimination and symmetry), discuss some examples, compare with related work and evaluate the performance on some synthetic data. Our results show considerable promise, reducing the error in grade predictions by a factor of 2 or more in many cases over the natural baseline of averaging peer grades.Comment: To appear in Proc. of ECAI 201