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221
Cooperative control and potential game
- IEEE Trans. Syst., Man, Cybern. B
, 2009
"... Abstract—We present a view of cooperative control using the language of learning in games. We review the game-theoretic concepts of potential and weakly acyclic games, and demonstrate how several cooperative control problems, such as consensus and dynamic sensor coverage, can be formulated in these ..."
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Cited by 32 (6 self)
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Abstract—We present a view of cooperative control using the language of learning in games. We review the game-theoretic concepts of potential and weakly acyclic games, and demonstrate how several cooperative control problems, such as consensus and dynamic sensor coverage, can be formulated in these settings. Motivated by this connection, we build upon game-theoretic concepts to better accommodate a broader class of cooperative control problems. In particular, we extend existing learning algorithms to accommodate restricted action sets caused by the limitations of agent capabilities and group-based decision making. Furthermore, we also introduce a new class of games called sometimes weakly acyclic games for time-varying objective functions and action sets, and provide distributed algorithms for convergence to an equilibrium. Index Terms—Cooperative control, game theory, learning in games, multi-agent systems. I.
Deploying power grid-integrated electric vehicles as a multi-agent system
- AAMAS
, 2011
"... Grid-Integrated Vehicles (GIVs) are plug-in Electric Drive Vehicles (EDVs) with power-management and other controls that allow them to respond to external commands sent by power-grid operators, or their affiliates, when parked and plugged-in to the grid. At a bare minimum, such GIVs should respond t ..."
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Cited by 27 (0 self)
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Grid-Integrated Vehicles (GIVs) are plug-in Electric Drive Vehicles (EDVs) with power-management and other controls that allow them to respond to external commands sent by power-grid operators, or their affiliates, when parked and plugged-in to the grid. At a bare minimum, such GIVs should respond to demand-management commands or pricing signals to delay, reduce or switch-off the rate of charging when the demand for electricity is high. In more advanced cases, these GIVs might sell both power and storage capacity back to the grid in any of the several electric power markets — a concept known as Vehicle-to-Grid power or V2G power. Although individual EDVs control too little power to sell in the market at an individual level, a large group of EDVs may form an aggregate or coalition that controls enough power to meaningfully sell, at a profit, in these markets.
Computer science and game theory
- Communications of the ACM
, 2008
"... Game theory has been playing an increasingly visible role in computer science, in areas as diverse as artificial intelligence, theory, and distributed systems, among others. I take stock of where most of the action has been in the past decade or so, and suggest that going forward, the most dramatic ..."
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Cited by 18 (1 self)
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Game theory has been playing an increasingly visible role in computer science, in areas as diverse as artificial intelligence, theory, and distributed systems, among others. I take stock of where most of the action has been in the past decade or so, and suggest that going forward, the most dramatic interaction between computer science and game theory could be around what might be called game theory pragmatics. 1
Auctions and Bidding: A Guide for Computer Scientists
"... There is a veritable menagerie of auctions — single-dimensional, multi-dimensional, single-sided, ..."
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Cited by 17 (0 self)
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There is a veritable menagerie of auctions — single-dimensional, multi-dimensional, single-sided,
Finding the optimal strategies in robotic patrolling with adversaries in topologically-represented environments
- in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA
"... Abstract — Using autonomous mobile robots to patrol en-vironments for detecting intruders is a topic of increasing relevance for its possible applications. A large part of strategies for mobile patrolling robots proposed so far adopt some kind of random movements. Although these strategies are unpre ..."
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Abstract — Using autonomous mobile robots to patrol en-vironments for detecting intruders is a topic of increasing relevance for its possible applications. A large part of strategies for mobile patrolling robots proposed so far adopt some kind of random movements. Although these strategies are unpre-dictable for an intruder, they are not always efficient in getting the patroller a large expected utility. In this paper we propose an approach that considers a model of the adversary in a game theoretic framework to find optimally-efficient patrolling strategies. We show that our approach extends those proposed in literature and we experimentally analyze some of its features. I.
Computing equilibria: A computational complexity perspective
, 2009
"... Computational complexity is the subfield of computer science that rigorously studies the intrinsic difficulty of computational problems. This survey explains how complexity theory defines “hard problems”; applies these concepts to several equilibrium computation problems; and discusses implications ..."
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Cited by 13 (2 self)
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Computational complexity is the subfield of computer science that rigorously studies the intrinsic difficulty of computational problems. This survey explains how complexity theory defines “hard problems”; applies these concepts to several equilibrium computation problems; and discusses implications for computation, games, and behavior. We assume
A qualitative vickrey auction
- University of Liverpool
, 2008
"... Restricting the preferences of the agents by assuming that their utility functions linearly depend on a payment allows for the positive results of the Vickrey auction and the Vickrey-Clarke-Groves mechanism. These results, however, are limited to settings where there is some commonly desired commodi ..."
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Restricting the preferences of the agents by assuming that their utility functions linearly depend on a payment allows for the positive results of the Vickrey auction and the Vickrey-Clarke-Groves mechanism. These results, however, are limited to settings where there is some commonly desired commodity or numeraire—money, shells, beads, etcetera—which is commensurable with utility. We propose a generalization of the Vickrey auction that does not assume that the agents ’ preferences are quasilinear, but nevertheless retains some of the Vickrey auction’s desirable proper-ties. In this auction, a bid can be any alternative, rather than just a monetary offer. As a consequence, the auction is also applicable to situa-tions where there is a fixed budget, or no numeraire is available at all (or it is undesirable to use payments for other reasons)—such as, for example, in the allocation of the task of contributing a module to an open-source project. We show that in two general settings, this qualitative Vickrey auction has a dominant-strategy equilibrium, invariably yields a weakly Pareto efficient outcome in this equilibrium, and is individually rational. In the first setting, the center has a linear preference order over a finite set of alternatives, and in the second setting, the bidders ’ preferences can be represented by continuous utility functions over a closed metric space of alternatives and the center’s utility is equipeaked. The traditional Vickrey auction turns out to be a special case of the qualitative Vickrey auction in this second setting. 1
Optimal Temporal Decoupling in Multiagent Systems
"... When agents need to interact in order to solve some (possibly common) problem, resolving potential conflicts beforehand is often preferred to coordination during execution. Agents may lose some flexibility, but their course of action will be more predictable and often also more efficient, obtaining ..."
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Cited by 10 (1 self)
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When agents need to interact in order to solve some (possibly common) problem, resolving potential conflicts beforehand is often preferred to coordination during execution. Agents may lose some flexibility, but their course of action will be more predictable and often also more efficient, obtaining a socially optimal outcome instead of a local optimum. One way to resolve conflicts beforehand is to give extra constraints to each of the agents such that when they all meet these constraints, the resulting execution is conflictfree. A set of constraints that meets this requirement is called a decoupling of the original problem; if it also maximizes the social welfare (i.e. the sum of the valuations of all the agents), it is called optimal. Representing interesting multiagent problems as a constraint problem, we show that finding an optimal decoupling is at least as hard as finding a solution for the constraint problem. We therefore focus on a constraint problem that is efficiently solvable, but still very relevant and interesting in the context of multiple agents executing their actions, i.e. the Simple Temporal Problem (STP). Two more technical results, then, are that we resolve the open question whether finding an optimal decoupling of the STP is NP-hard (it is), and if all agents have linear valuation functions, this decoupling problem can be solved efficiently.
Bayesian Action-Graph Games
"... Games of incomplete information, or Bayesian games, are an important gametheoretic model and have many applications in economics. We propose Bayesian action-graph games (BAGGs), a novel graphical representation for Bayesian games. BAGGs can represent arbitrary Bayesian games, and furthermore can com ..."
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Cited by 9 (1 self)
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Games of incomplete information, or Bayesian games, are an important gametheoretic model and have many applications in economics. We propose Bayesian action-graph games (BAGGs), a novel graphical representation for Bayesian games. BAGGs can represent arbitrary Bayesian games, and furthermore can compactly express Bayesian games exhibiting commonly encountered types of structure including symmetry, action- and type-specific utility independence, and probabilistic independence of type distributions. We provide an algorithm for computing expected utility in BAGGs, and discuss conditions under which the algorithm runs in polynomial time. Bayes-Nash equilibria of BAGGs can be computed by adapting existing algorithms for complete-information normal form games and leveraging our expected utility algorithm. We show both theoretically and empirically that our approaches improve significantly on the state of the art. 1
