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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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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
A Revealed Preference Approach to Computational Complexity in Economics
, 2010
"... One of the main building blocks of economics is the theory of the consumer, which postulates that consumers are utility maximizing. However, from a computational perspective, this model is called into question because the task of utility maximization subject to a budget constraint is computationally ..."
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One of the main building blocks of economics is the theory of the consumer, which postulates that consumers are utility maximizing. However, from a computational perspective, this model is called into question because the task of utility maximization subject to a budget constraint is computationally hard in the worstcase under reasonable assumptions. In this paper, we study the empirical consequences of strengthening consumer choice theory to enforce that utilities are computationally easy to maximize. We prove the possibly surprising result that computational constraints have no empirical consequences whatsoever for consumer choice theory. That is, a data set is consistent with a utility maximizing consumer if and only if a data set is consistent with a utility maximizing consumer having a utility function that can be maximized in strongly polynomial time. Our result motivates a general approach for posing questions about the empirical content of computational constraints: the revealed preference approach to computational complexity. The approach complements the conventional worstcase view of computational complexity in important ways, and is methodologically close to mainstream economics.
An algorithmic game theory primer
, 2008
"... We give a brief and biased survey of the past, present, and future of research on the interface of theoretical computer science and game theory. ..."
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We give a brief and biased survey of the past, present, and future of research on the interface of theoretical computer science and game theory.
Essentials of game theory
, 2008
"... doi:10.1145/1378704.1378721 The most dramatic interaction between CS and GT may involve gametheory pragmatics. ..."
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doi:10.1145/1378704.1378721 The most dramatic interaction between CS and GT may involve gametheory pragmatics.
Cacheaware user association in backhaulconstrained small cell networks
 in the 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt 2014
, 2014
"... AbstractAnticipating multimedia file requests via caching at the small cell base stations (SBSs) of a cellular network has emerged as a promising technique for optimizing the quality of service (QoS) of wireless user equipments (UEs). However, developing efficient caching strategies must properly ..."
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AbstractAnticipating multimedia file requests via caching at the small cell base stations (SBSs) of a cellular network has emerged as a promising technique for optimizing the quality of service (QoS) of wireless user equipments (UEs). However, developing efficient caching strategies must properly account for specific small cell constraints, such as backhaul congestion and limited storage capacity. In this paper, we address the problem of devising a usercell association, in which the SBSs exploit caching capabilities to overcome the backhaul capacity limitations and enhance the users' QoS. In the proposed approach, the SBSs individually decide on which UEs to service based on both content availability and on the data rates they can deliver, given the interference and backhaul capacity limitations. We formulate the problem as a onetomany matching game between SBSs and UEs. To solve this game, we propose a distributed algorithm, based on the deferred acceptance scheme, that enables the players (i.e., UEs and SBSs) to selforganize into a stable matching, in a reasonable number of algorithm iterations. Simulation results show that the proposed cell association scheme yields significant gains, reaching up to 21% improvement compared to a traditional cell association techniques with no caching considerations.
The Empirical Implications of Rank in Bimatrix Games
, 2013
"... We study the structural complexity of bimatrix games, formalized via rank, from an empirical perspective. We consider a setting where we have data on player behavior in diverse strategic situations, but where we do not observe the relevant payoff functions. We prove that high complexity (high rank) ..."
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We study the structural complexity of bimatrix games, formalized via rank, from an empirical perspective. We consider a setting where we have data on player behavior in diverse strategic situations, but where we do not observe the relevant payoff functions. We prove that high complexity (high rank) has empirical consequences when arbitrary data is considered. Additionally, we prove that, in more restrictive classes of data (termed laminar), any observation is rationalizable using a lowrank game: specifically a zerosum game. Hence complexity as a structural property of a game is not always testable. Finally, we prove a general result connecting the structure of the feasible data sets with the highest rank that may be needed to rationalize a set of observations.
Complexity of evolutionary equilibria in static fitness landscapes
, 2013
"... A fitness landscape is a genetic space – with two genotypes adjacent if they differ in a single locus – and a fitness function. Evolutionary dynamics produce a flow on this landscape from lower fitness to higher; reaching equilibrium only if a local fitness peak is found. I use computational complex ..."
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A fitness landscape is a genetic space – with two genotypes adjacent if they differ in a single locus – and a fitness function. Evolutionary dynamics produce a flow on this landscape from lower fitness to higher; reaching equilibrium only if a local fitness peak is found. I use computational complexity to question the common assumption that evolution on static fitness landscapes can quickly reach a local fitness peak. I do this by showing that the popular NK model of rugged fitness landscapes is PLScomplete for K ≥ 2; the reduction from Weighted 2SAT is a bijection on adaptive walks, so there are NK fitness landscapes where every adaptive path from some vertices is of exponential length. Alternatively – under the standard complexity theoretic assumption that there are problems in PLS not solvable in polynomial time – this means that there are no evolutionary dynamics (known, or to be discovered, and not necessarily following adaptive paths) that can converge to a local fitness peak on all NK landscapes with K = 2. Applying results from the analysis of simplex algorithms, I show that there exist singlepeaked landscapes with no reciprocal sign epistasis where the expected length of an adaptive path following strong selection weak mutation dynamics is eO(n 1/3) even though an adaptive path to the optimum of length less than n is available from every vertex. The technical results are written to be accessible to mathematical biologists without a computer science background, and the biological literature is summarized for the convenience of nonbiologists with the aim to open a constructive dialogue between the two disciplines.
Digital Repository @ Iowa State University
, 2013
"... Computation and analysis of evolutionary game dynamics ..."
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