5,266 research outputs found

    Settling Some Open Problems on 2-Player Symmetric Nash Equilibria

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    Over the years, researchers have studied the complexity of several decision versions of Nash equilibrium in (symmetric) two-player games (bimatrix games). To the best of our knowledge, the last remaining open problem of this sort is the following; it was stated by Papadimitriou in 2007: find a non-symmetric Nash equilibrium (NE) in a symmetric game. We show that this problem is NP-complete and the problem of counting the number of non-symmetric NE in a symmetric game is #P-complete. In 2005, Kannan and Theobald defined the "rank of a bimatrix game" represented by matrices (A, B) to be rank(A+B) and asked whether a NE can be computed in rank 1 games in polynomial time. Observe that the rank 0 case is precisely the zero sum case, for which a polynomial time algorithm follows from von Neumann's reduction of such games to linear programming. In 2011, Adsul et. al. obtained an algorithm for rank 1 games; however, it does not solve the case of symmetric rank 1 games. We resolve this problem

    On kernels, defaults and even graphs

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    Extensions in prerequisite-free, disjunction-free default theories have been shown to be in direct correspondence with kernels of directed graphs; hence default theories without odd cycles always have a ``standard'' kind of an extension. We show that, although all ``standard'' extensions can be enumerated explicitly, several other problems remain intractable for such theories: Telling whether a non-standard extension exists, enumerating all extensions, and finding the minimal standard extension. We also present a new graph-theoretic algorithm, based on vertex feedback sets, for enumerating all extensions of a general prerequisite-free, disjunction-free default theory (possibly with odd cycles). The algorithm empirically performs well for quite large theories

    Critical slowing down in polynomial time algorithms

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    Combinatorial optimization algorithms which compute exact ground state configurations in disordered magnets are seen to exhibit critical slowing down at zero temperature phase transitions. Using arguments based on the physical picture of the model, including vanishing stiffness on scales beyond the correlation length and the ground state degeneracy, the number of operations carried out by one such algorithm, the push-relabel algorithm for the random field Ising model, can be estimated. Some scaling can also be predicted for the 2D spin glass.Comment: 4 pp., 3 fig

    Swampland Criteria and Constraints on Inflation in a f(R,T)f(R,T) Gravity Theory

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    In this paper, we worked in the framework of an inflationary f(R,T)f(R,T) theory, in the presence of a canonical scalar field. More specifically, the f(R,T)=γR+2καTf(R,T)=\gamma R+2\kappa\alpha T gravity. The values of the dimensionless parameters α\alpha and γ\gamma are taken to be α≥0\alpha \geq 0 and 0<γ≤10 < \gamma \leq 1. The motivation for that study was the striking similarities between the slow-roll parameters of the inflationary model used in this work and the ones obtained by the rescaled Einstein-Hilbert gravity inflation f(R)=αRf(R)=\alpha R. We examined a variety of potentials to determine if they agree with the current Planck Constraints. In addition, we checked whether these models satisfy the Swampland Criteria and we specified the exact region of the parameter space that produces viable results for each model. As we mention in Section IV the inflationary f(R,T)f(R,T) theory used in this work can not produce a positive nTn_T which implies that the stochastic gravitational wave background will not be detectable.Comment: IJMPD Accepte

    A Direct Reduction from k-Player to 2-Player Approximate Nash Equilibrium

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    We present a direct reduction from k-player games to 2-player games that preserves approximate Nash equilibrium. Previously, the computational equivalence of computing approximate Nash equilibrium in k-player and 2-player games was established via an indirect reduction. This included a sequence of works defining the complexity class PPAD, identifying complete problems for this class, showing that computing approximate Nash equilibrium for k-player games is in PPAD, and reducing a PPAD-complete problem to computing approximate Nash equilibrium for 2-player games. Our direct reduction makes no use of the concept of PPAD, thus eliminating some of the difficulties involved in following the known indirect reduction.Comment: 21 page

    Quenched Random Graphs

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    Spin models on quenched random graphs are related to many important optimization problems. We give a new derivation of their mean-field equations that elucidates the role of the natural order parameter in these models.Comment: 9 pages, report CPTH-A264.109

    Qualitative Analysis of Partially-observable Markov Decision Processes

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    We study observation-based strategies for partially-observable Markov decision processes (POMDPs) with omega-regular objectives. An observation-based strategy relies on partial information about the history of a play, namely, on the past sequence of observations. We consider the qualitative analysis problem: given a POMDP with an omega-regular objective, whether there is an observation-based strategy to achieve the objective with probability~1 (almost-sure winning), or with positive probability (positive winning). Our main results are twofold. First, we present a complete picture of the computational complexity of the qualitative analysis of POMDP s with parity objectives (a canonical form to express omega-regular objectives) and its subclasses. Our contribution consists in establishing several upper and lower bounds that were not known in literature. Second, we present optimal bounds (matching upper and lower bounds) on the memory required by pure and randomized observation-based strategies for the qualitative analysis of POMDP s with parity objectives and its subclasses
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