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69
Distributed Implementations of Vickrey-Clarke-Groves Mechanisms
- in Proc. 3rd Int. Joint Conf. on Autonomous Agents and Multi Agent Systems
, 2004
"... Mechanism design (MD) provides a useful method to implement outcomes with desirable properties in systems with self-interested computational agents. One drawback, however, is that computation is implicitly centralized in MD theory, with a central planner taking all decisions. We consider distributed ..."
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Cited by 49 (10 self)
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Mechanism design (MD) provides a useful method to implement outcomes with desirable properties in systems with self-interested computational agents. One drawback, however, is that computation is implicitly centralized in MD theory, with a central planner taking all decisions. We consider distributed implementations, in which the outcome is determined by the self-interested agents themselves. Clearly this introduces new opportunities for manipulation. We propose a number of principles to guide the distribution of computation, focusing in particular on Vickrey-Clarke-Groves mechanisms for implementing outcomes that maximize total value across agents. Our solutions bring the complete implementation into an ex post Nash equilibrium.
A Survey on Sensor Networks from a Multi-Agent perspective
"... Sensor networks arise as one of the most promising technologies for the next decades. The recent emergence of small and inexpensive sensors based upon microelectromechanical system (MEMS) ease the development and proliferation of this kind of networks in a wide range of real-world applications. Mult ..."
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Cited by 26 (0 self)
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Sensor networks arise as one of the most promising technologies for the next decades. The recent emergence of small and inexpensive sensors based upon microelectromechanical system (MEMS) ease the development and proliferation of this kind of networks in a wide range of real-world applications. Multi-Agent systems (MAS) have been identified as one of the most suitable technologies to contribute to this domain due to their appropriateness for modeling autonomous self-aware sensors in a flexible way. Firstly, this survey summarizes the actual challenges and research areas concerning sensor networks while identifying the most relevant MAS contributions. Secondly, we propose a taxonomy for sensor networks that classifies them depending on their features (and the research problems they pose). Finally, we identify some open future research directions and opportunities for MAS research. 1.
Collusion-resistant, Incentive-compatible Feedback Payments
, 2007
"... Online reputation mechanisms need honest feedback to function effectively. Self-interested agents report the truth only when explicit rewards offset the potential gains obtained from lying. Feedback payment schemes (monetary rewards for submitted feedback) can make truth-telling rational based on th ..."
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Cited by 18 (3 self)
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Online reputation mechanisms need honest feedback to function effectively. Self-interested agents report the truth only when explicit rewards offset the potential gains obtained from lying. Feedback payment schemes (monetary rewards for submitted feedback) can make truth-telling rational based on the correlation between the reports of different buyers. In this paper we investigate incentive-compatible payment mechanisms that are also resistant to collusion: groups of agents cannot collude on a lying strategy without suffering monetary losses. We analyze several scenarios, where, for example, some or all of the agents collude. For each scenario we investigate both existential and implementation problems. Throughout the paper we use automated mechanism design to compute the best possible mechanism for a given setting.
Dynamic bayesian combination of multiple imperfect classifiers. arXiv preprint arXiv:1206.1831
, 2012
"... Classifier combination methods need to make best use of the outputs of multiple, imperfect classifiers to enable higher accuracy classifications. In many situations, such as when human decisions need to be combined, the base decisions can vary enormously in reliability. A Bayesian approach to such u ..."
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Cited by 16 (3 self)
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Classifier combination methods need to make best use of the outputs of multiple, imperfect classifiers to enable higher accuracy classifications. In many situations, such as when human decisions need to be combined, the base decisions can vary enormously in reliability. A Bayesian approach to such uncertain combination allows us to infer the differences in performance between individuals and to in-corporate any available prior knowledge about their abilities when training data is sparse. In this paper we explore Bayesian classifier combination, using the com-putationally efficient framework of variational Bayesian inference. We apply the approach to real data from a large citizen science project, Galaxy Zoo Supernovae, and show that our method far outperforms other established approaches to imper-fect decision combination. We go on to analyse the putative community structure of the decision makers, based on their inferred decision making strategies, and show that natural groupings are formed. 1
Efficient and Strategyproof Spectrum Allocations in Multichannel Wireless Networks
"... Abstract—In this paper, we study the spectrum assignment problem for wireless access networks. We assume that each secondary user will bid a certain value for exclusive usage of some spectrum channels for a certain time period or for a certain time duration. A secondary user may also require the exc ..."
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Cited by 15 (4 self)
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Abstract—In this paper, we study the spectrum assignment problem for wireless access networks. We assume that each secondary user will bid a certain value for exclusive usage of some spectrum channels for a certain time period or for a certain time duration. A secondary user may also require the exclusive usage of a subset of channels, or require the exclusive usage of a certain number of channels. Thus, several versions of problems are formulated under various different assumptions. For the majority of problems, we design PTAS or efficient constant-approximation algorithms such that overall profit is maximized. Here, the profit is defined as the total bids of all satisfied secondary users. As a side product of our algorithms, we are able to show that a previously studied Scheduling Split Interval Problem (SSIP) [2], in which each job is composed of t intervals, cannot be approximated within Oðt1 Þ for any small>0 unless NP ZPP. Opportunistic spectrum usage, although a promising technology, could suffer from the selfish behavior of secondary users. In order to improve opportunistic spectrum usage, we then propose to combine the game theory with wireless modeling. We show how to design a truthful mechanism based on all of these algorithms such that the best strategy of each secondary user to maximize its own profit is to truthfully report its actual bid.
Performance Analysis of Allocation Policies for InterGrid Resource Provisioning
, 2008
"... Several Grids have been established and used for varying science applications during the last years. Most of these Grids, however, work in isolation and with different utilisation levels. Previous work introduced an architecture and a mechanism to enable resource sharing amongst Grids. It demonstrat ..."
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Cited by 13 (4 self)
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Several Grids have been established and used for varying science applications during the last years. Most of these Grids, however, work in isolation and with different utilisation levels. Previous work introduced an architecture and a mechanism to enable resource sharing amongst Grids. It demonstrated that there can be benefits for a Grid to offload requests or provide spare resources to another Grid, thus reducing the cost of over-provisioning. These benefits derive from the fact that resource utilisation within a Grid has fixed and operational costs such as those with electricity providers and system administrators. In this work, we address the problem of resource provisioning to Grid applications in multiple-Grid environments. The provisioning is carried out based on availability information obtained from queueing-based resource management systems deployed at the provider sites who are the participants of the Grids. We evaluate the performance of different allocation policies. In contrast to existing work on load sharing across Grids, the policies described here take into account the local load of resource providers, imprecise availability information and the monetary compensation of providers. In addition, we evaluate these policies along with mechanism that allows resource sharing amongst Grids. Experimental results obtained through simulation show that the mechanism and policies are effective in redirecting requests thus improving the applications’ average weighted response time.
Computational mechanism design for information fusion within sensor networks
- In Proceedings of The 9th International Conference on Information Fusion
, 2006
"... Abstract- Conventional centralised information fusion and control architectures will be challenged by developments in sensor networks that allow sophisticated autonomous sensors, owned by different stakeholders with individual goals, to interact and share information. Given this, we advocate the use ..."
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Cited by 11 (3 self)
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Abstract- Conventional centralised information fusion and control architectures will be challenged by developments in sensor networks that allow sophisticated autonomous sensors, owned by different stakeholders with individual goals, to interact and share information. Given this, we advocate the use of tools and techniques from computational mechanism design (CMD), a field at the intersection of computer science, game theory and economics, to address the challenges posed by these networks. In particular, CMD allows us to engineer networks with desirable system-wide properties, in which sensors act as rational selfish agents, each attempting to fulfill their own individuals goals through the exchange of observations and information. In this paper, we present our work developing such networks. Specifically, we discuss our development of a generic and principled information valuation metric for sensor networks and we report our experiences applying it within a real world information fusion sensor network scenario.
Design Space Analysis for Modeling Incentives in Distributed Systems
"... Distributed systems without a central authority, such as peer-topeer (P2P) systems, employ incentives to encourage nodes to follow the prescribed protocol. Game-theoretic analysis is often used to evaluate incentives in such systems. However, most gametheoretic analyses of distributed systems do not ..."
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Cited by 8 (2 self)
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Distributed systems without a central authority, such as peer-topeer (P2P) systems, employ incentives to encourage nodes to follow the prescribed protocol. Game-theoretic analysis is often used to evaluate incentives in such systems. However, most gametheoretic analyses of distributed systems do not adequately model the repeated interactions of nodes inherent in such systems. We present a game-theoretic analysis of a popular P2P protocol, Bit-Torrent, that models the repeated interactions in such protocols. We also note that an analytical approach for modeling incentives is often infeasible given the complicated nature of most deployed protocols. In order to comprehensively model incentives in complex protocols, we propose a simulation-based method, which we call Design Space Analysis (DSA). DSA provides a tractable analysis of competing protocol variants within a detailed design space. We apply DSA to P2P file swarming systems. With extensive simulations we analyze a wide-range of protocol variants and gain insights into their robustness and performance. To validate these results and to demonstrate the efficacy of DSA, we modify an instrumented BitTorrent client and evaluate protocols discovered using DSA. We show that they yield higher system performance and robustness relative to the reference implementation.
Improving efficiency and fairness in p2p systems with effort-based incentives
- In Proceedings of ICC
, 2010
"... Abstract — 1 Most P2P systems that have any kind of incentive mechanism reward peers ’ contribution in terms of uploaded volume. Due to the disparity in bandwidth capacity between P2P users on the Internet, the common effect of such mechanisms is that the fastest peers reap the highest benefits. We ..."
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Cited by 8 (3 self)
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Abstract — 1 Most P2P systems that have any kind of incentive mechanism reward peers ’ contribution in terms of uploaded volume. Due to the disparity in bandwidth capacity between P2P users on the Internet, the common effect of such mechanisms is that the fastest peers reap the highest benefits. We take a different approach and study how to incentivize cooperation in P2P systems based on peers ’ effort, i.e., contribution relative to capacity. We make the following contributions: 1) we propose that volume-based incentive schemes in P2P systems unnecessarily punish slow peers and decrease overall system performance; 2) we advocate that principles from an alternate economic vision, Participatory Economics (Parecon), can inspire systems which are fair and ensure maximization of the social welfare, while being efficient at the same time and 3) we present simulation results of applied principles from Parecon to two popular real life systems: a) the popular file sharing BitTorrent protocol, b) a generic credit based sharing ratio enforcement scheme. Our approach yields higher system performance and fairness for both, and offers interesting new insights into P2P incentive design. I.
