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Electronic colloquium on computational complexity

Parallel Repetition of Fortified Games.

Dana Moshkovitz

Published Jan 1, 2014• 1 citation
OpenAlex

Abstract

The Parallel Repetition Theorem upper-bounds the value of a repeated (tensored) two prover game G⊗k in terms of the value of the game G and the number of repetitions k. Contrary to what one might have guessed, the value of G⊗k is not val(G), but rather a more complicated expression depending on properties of G. Indeed, there are numerous works aiming to understand the value of repeated games, both for general games G and for special cases. A case of particular interest is that of projection games, where the answer of the first prover determines at most one acceptable answer for the second prover. In this work we give a simple transformation, which we call “fortification”, that can be applied to any projection game. We show that for fortified games G, the value of the k-repeated game is approximately val(G). This results in nearly a quadratic improvement in the size of projection PCP with the lowest error known today. Unlike previous proofs of the parallel repetition theorem that relied on information theory or linear algebra, our proof is purely combinatorial and quite short. We then discuss the problem of derandomizing parallel repetition, and the limitations of the fortification idea in this setting. We point out a connection between the problem of derandomizing parallel repetition and the problem of composition. This connection could shed light on the so-called Projection Games Conjecture, which asks for projection PCP with minimal error. ∗dmoshkov@csail.mit.edu. Department of Electrical Engineering and Computer Science, MIT. This material is based upon work supported by the National Science Foundation under Grant Number 1218547.

Related papers

Parallel Repetition from Fortification

Dana Moshkovitz

The Parallel Repetition Theorem upper-bounds the value of a repeated (tensored) two prover game in terms of the value of the base game and the number of repetitions. In this work we give a simple transformation on games -- "fortification" -- and show that for fortified games, the value of the repeated game decreases perfectly exponentially with the number of repetitions, up to an arbitrarily small additive error. Our proof is combinatorial and short. As corollaries, we obtain: (1) Starting from a PCP Theorem with soundness error bounded away from 1, we get a PCP with arbitrarily small constant soundness error. In particular, starting with the combinatorial PCP of Dinur, we get a combinatorial PCP with low error. The latter can be used for hardness of approximation as in the work of Håstad. (2) Starting from the work of the author and Raz, we get a projection PCP theorem with the smallest soundness error known today. The theorem yields nearly a quadratic improvement in the size compared to previous work. We then discuss the problem of derandomizing parallel repetition, and the limitations of the fortification idea in this setting. We point out a connection between the problem of derandomizing parallel repetition and the problem of composition. This connection could shed light on the so-called Projection Games Conjecture, which asks for projection PCP with minimal error.

Annual Symposium on Foundations of Computer Science•Oct 1, 2014•13 citations

Parallel repetition via fortification: analytic view and the quantum case

Mohammad Bavarian, Thomas Vidick, Henry Yuen

In a recent work, Moshkovitz [FOCS '14] presented a transformation on two-player games called "fortification", and gave an elementary proof of an (exponential decay) parallel repetition theorem for fortified two-player projection games. In this paper, we give an analytic reformulation of Moshkovitz's fortification framework, which was originally cast in combinatorial terms. This reformulation allows us to expand the scope of the fortification method to new settings. First, we show any game (not just projection games) can be fortified, and give a simple proof of parallel repetition for general fortified games. Then, we prove parallel repetition and fortification theorems for games with players sharing quantum entanglement, as well as games with more than two players. This gives a new gap amplification method for general games in the quantum and multiplayer settings, which has recently received much interest. An important component of our work is a variant of the fortification transformation, called "ordered fortification", that preserves the entangled value of a game. The original fortification of Moshkovitz does not in general preserve the entangled value of a game, and this was a barrier to extending the fortification framework to the quantum setting.

arXiv:1603.05349•Mar 17, 2016•6 citations

Parallel Repetition via Fortification: Analytic View and the Quantum Case

Mohammad Bavarian, Thomas Vidick, Henry Yuen

In a recent work, Moshkovitz [FOCS'14] presented a transformation n two-player games called "fortification", and gave an elementary proof of an (exponential decay) parallel repetition theorem for fortified two-player projection games. In this paper, we give an analytic reformulation of Moshkovitz's fortification framework, which was originally cast in combinatorial terms. This reformulation allows us to expand the scope of the fortification method to new settings. First, we show any game (not just projection games) can be fortified, and give a simple proof of parallel repetition for general fortified games. Then, we prove parallel repetition and fortification theorems for games with players sharing quantum entanglement, as well as games with more than two players. This gives a new gap amplification method for general games in the quantum and multiplayer settings, which has recently received much interest. An important component of our work is a variant of the fortification transformation, called "ordered fortification", that preserves the entangled value of a game. The original fortification of Moshkovitz does not in general preserve the entangled value of a game, and this was a barrier to extending the fortification framework to the quantum setting.

Leibniz international proceedings in informatics•Jan 1, 2017•0 citations

A k-PROVERS PARALLEL REPETITION THEOREM FOR A VERSION OF NO-SIGNALING MODEL

Ricky Rosen

The parallel repetition theorem states that for any two provers one round game with value at most 1 - ∊ (for ∊ < 1/2), the value of the game repeated n times in parallel is at most (1 - ∊3)Ω(n/ log s) where s is the size of the answers set [9, 12]. It is not known how the value of the game decreases when there are three or more players. In this paper we address the problem of the error decrease of parallel repetition game for k-provers where k > 2. We consider a special case of the No-Signaling model and show that the error of the parallel repetition of k-provers one round game, for k > 2, in this model, decreases exponentially depending only on the error of the original game and on the number of repetitions. There were no prior results for k-provers parallel repetition for k > 2 in any model.

Discrete Mathematics Algorithms and Applications•Dec 1, 2010•0 citations

Parallel Repetition of Prover-Verifier Quantum Interactions

Abel Molina

In this thesis, we answer several questions about the behaviour of prover-verifier interactions under parallel repetition when quantum information is allowed, and the verifier acts independently in them. \n \nWe first consider the case in which a value is associated with each of the possible outcomes of an interaction. We prove that it is not possible for the prover to improve on the optimum average value per repetition by repeating the protocol multiple times in parallel. \n \nWe look then at games in which the outcomes are classified into two types, winning outcomes and losing outcomes. We ask what is the optimal probability for the prover of winning at least k times out of n parallel repetitions, given that the optimal probability of winning when only one repetition is considered is p. A reasonable conjecture for the answer would be the answer when it is optimal for the prover to act independently. This is known to be the correct answer when k=n. We will show how this cannot be extended to the general case, presenting an example of an interaction with k=1,n=2 in which p is approximately 0.85, but it is possible to always win at least once. We will then give some upper bounds on the optimal probability for the prover of winning k times out of n parallel repetitions. These bounds are expressed as a function of p. \n \nFinally, we connect our results to the study of error reduction for quantum interactive proofs using parallel repetition.

•Jan 1, 2011•0 citations

A Counterexample to Strong Parallel Repetition

Ran Raz

The parallel repetition theorem states that, for any two-prover game with value $1-\epsilon$ (for, say, $\epsilon\leq1/2$), the value of the game repeated in parallel n times is at most $(1-\epsilon^c)^{\Omega(n/s)}$, where s is the answer's length (of the original game) and c is a universal constant [R. Raz, SIAM J. Comput., 27 (1998), pp. 763–803]. Several researchers asked whether this bound could be improved to $(1-\epsilon)^{\Omega(n/s)}$; this question is usually referred to as the strong parallel repetition problem. We show that the answer to this question is negative. More precisely, we consider the odd cycle game of size m, a two-prover game with value $1-1/2m$. We show that the value of the odd cycle game repeated in parallel n times is at least $1-(1/m)\cdot O(\sqrt{n})$. This implies that, for large enough n (say, $n\geq\Omega(m^2)$), the value of the odd cycle game repeated in parallel n times is at least $(1-1/4m^2)^{O(n)}$. Thus the following hold. 1. For parallel repetition of general games, the bounds of $(1-\epsilon^c)^{\Omega(n/s)}$ given in [R. Raz, SIAM J. Comput., 27 (1998), pp. 763–803; T. Holenstein, in Proceedings of STOC 2002, ACM, New York, 2002, pp. 767–775] are of the right form, up to determining the exact value of the constant $c\geq2$. 2. For parallel repetition of XOR games, unique games, and projection games, the bounds of $(1-\epsilon^2)^{\Omega(n)}$ given in [U. Feige, G. Kindler, and R. O'Donnell, in Proceedings of CCC 2007, IEEE Computer Society, Washington, DC, 2007, pp. 179–192] (for XOR games) and in [A. Rao, in Proceedings of STOC 2008, ACM, New York, 2008, pp. 1–10] (for unique and projection games) are tight. 3. For parallel repetition of the odd cycle game, the bound of $1-(1/m)\cdot\tilde{\Omega}(\sqrt{n})$ given in [U. Feige, G. Kindler, and R. O'Donnell, in Proceedings of CCC 2007, IEEE Computer Society, Washington, DC, 2007, pp. 179–192] is almost tight. A major motivation for the recent interest in the strong parallel repetition problem is that a strong parallel repetition theorem would have implied that the unique game conjecture is equivalent to the NP hardness of distinguishing between instances of Max-Cut that are at least $1-\epsilon^2$ satisfiable from instances that are at most $1-(2/\pi)\cdot\epsilon$ satisfiable. Our results suggest that this cannot be proved just by improving the known bounds on parallel repetition.

Annual Symposium on Foundations of Computer Science•Oct 1, 2008•82 citations
The Parallel Repetition Theorem upper-bounds the value of a repeated (tensored) two prover game G⊗k in terms of the value of the game G and the number of repetitions k. Contrary to what one might have guessed, the value of G⊗k is not val(G), but rather a more complicated expression depending on properties of G. Indeed, there are numerous works aiming to understand the value of repeated games, both for general games G and for special cases. A case of particular interest is that of projection games, where the answer of the first prover determines at most one acceptable answer for the second prover. In this work we give a simple transformation, which we call “fortification”, that can be applied to any projection game. We show that for fortified games G, the value of the k-repeated game is approximately val(G). This results in nearly a quadratic improvement in the size of projection PCP with the lowest error known today. Unlike previous proofs of the parallel repetition theorem that relied on information theory or linear algebra, our proof is purely combinatorial and quite short. We then discuss the problem of derandomizing parallel repetition, and the limitations of the fortification idea in this setting. We point out a connection between the problem of derandomizing parallel repetition and the problem of composition. This connection could shed light on the so-called Projection Games Conjecture, which asks for projection PCP with minimal error. ∗dmoshkov@csail.mit.edu. Department of Electrical Engineering and Computer Science, MIT. This material is based upon work supported by the National Science Foundation under Grant Number 1218547.
The Parallel Repetition Theorem upper-bounds the value of a repeated (tensored) two prover game in terms of the value of the base game and the number of repetitions. In this work we give a simple transformation on games -- "fortification" -- and show that for fortified games, the value of the repeated game decreases perfectly exponentially with the number of repetitions, up to an arbitrarily small additive error. Our proof is combinatorial and short. As corollaries, we obtain: (1) Starting from a PCP Theorem with soundness error bounded away from 1, we get a PCP with arbitrarily small constant soundness error. In particular, starting with the combinatorial PCP of Dinur, we get a combinatorial PCP with low error. The latter can be used for hardness of approximation as in the work of Håstad. (2) Starting from the work of the author and Raz, we get a projection PCP theorem with the smallest soundness error known today. The theorem yields nearly a quadratic improvement in the size compared to previous work. We then discuss the problem of derandomizing parallel repetition, and the limitations of the fortification idea in this setting. We point out a connection between the problem of derandomizing parallel repetition and the problem of composition. This connection could shed light on the so-called Projection Games Conjecture, which asks for projection PCP with minimal error.
In a recent work, Moshkovitz [FOCS '14] presented a transformation on two-player games called "fortification", and gave an elementary proof of an (exponential decay) parallel repetition theorem for fortified two-player projection games. In this paper, we give an analytic reformulation of Moshkovitz's fortification framework, which was originally cast in combinatorial terms. This reformulation allows us to expand the scope of the fortification method to new settings. First, we show any game (not just projection games) can be fortified, and give a simple proof of parallel repetition for general fortified games. Then, we prove parallel repetition and fortification theorems for games with players sharing quantum entanglement, as well as games with more than two players. This gives a new gap amplification method for general games in the quantum and multiplayer settings, which has recently received much interest. An important component of our work is a variant of the fortification transformation, called "ordered fortification", that preserves the entangled value of a game. The original fortification of Moshkovitz does not in general preserve the entangled value of a game, and this was a barrier to extending the fortification framework to the quantum setting.
In a recent work, Moshkovitz [FOCS'14] presented a transformation n two-player games called "fortification", and gave an elementary proof of an (exponential decay) parallel repetition theorem for fortified two-player projection games. In this paper, we give an analytic reformulation of Moshkovitz's fortification framework, which was originally cast in combinatorial terms. This reformulation allows us to expand the scope of the fortification method to new settings. First, we show any game (not just projection games) can be fortified, and give a simple proof of parallel repetition for general fortified games. Then, we prove parallel repetition and fortification theorems for games with players sharing quantum entanglement, as well as games with more than two players. This gives a new gap amplification method for general games in the quantum and multiplayer settings, which has recently received much interest. An important component of our work is a variant of the fortification transformation, called "ordered fortification", that preserves the entangled value of a game. The original fortification of Moshkovitz does not in general preserve the entangled value of a game, and this was a barrier to extending the fortification framework to the quantum setting.
The parallel repetition theorem states that for any two provers one round game with value at most 1 - ∊ (for ∊ < 1/2), the value of the game repeated n times in parallel is at most (1 - ∊3)Ω(n/ log s) where s is the size of the answers set [9, 12]. It is not known how the value of the game decreases when there are three or more players. In this paper we address the problem of the error decrease of parallel repetition game for k-provers where k > 2. We consider a special case of the No-Signaling model and show that the error of the parallel repetition of k-provers one round game, for k > 2, in this model, decreases exponentially depending only on the error of the original game and on the number of repetitions. There were no prior results for k-provers parallel repetition for k > 2 in any model.
In this thesis, we answer several questions about the behaviour of prover-verifier interactions under parallel repetition when quantum information is allowed, and the verifier acts independently in them. \n \nWe first consider the case in which a value is associated with each of the possible outcomes of an interaction. We prove that it is not possible for the prover to improve on the optimum average value per repetition by repeating the protocol multiple times in parallel. \n \nWe look then at games in which the outcomes are classified into two types, winning outcomes and losing outcomes. We ask what is the optimal probability for the prover of winning at least k times out of n parallel repetitions, given that the optimal probability of winning when only one repetition is considered is p. A reasonable conjecture for the answer would be the answer when it is optimal for the prover to act independently. This is known to be the correct answer when k=n. We will show how this cannot be extended to the general case, presenting an example of an interaction with k=1,n=2 in which p is approximately 0.85, but it is possible to always win at least once. We will then give some upper bounds on the optimal probability for the prover of winning k times out of n parallel repetitions. These bounds are expressed as a function of p. \n \nFinally, we connect our results to the study of error reduction for quantum interactive proofs using parallel repetition.
The parallel repetition theorem states that, for any two-prover game with value 1−ϵ1-\epsilon1−ϵ (for, say, ϵ≤1/2\epsilon\leq1/2ϵ≤1/2), the value of the game repeated in parallel n times is at most (1−ϵc)Ω(n/s)(1-\epsilon^c)^{\Omega(n/s)}(1−ϵc)Ω(n/s), where s is the answer's length (of the original game) and c is a universal constant [R. Raz, SIAM J. Comput., 27 (1998), pp. 763–803]. Several researchers asked whether this bound could be improved to (1−ϵ)Ω(n/s)(1-\epsilon)^{\Omega(n/s)}(1−ϵ)Ω(n/s); this question is usually referred to as the strong parallel repetition problem. We show that the answer to this question is negative. More precisely, we consider the odd cycle game of size m, a two-prover game with value 1−1/2m1-1/2m1−1/2m. We show that the value of the odd cycle game repeated in parallel n times is at least 1−(1/m)⋅O(n)1-(1/m)\cdot O(\sqrt{n})1−(1/m)⋅O(n​). This implies that, for large enough n (say, n≥Ω(m2)n\geq\Omega(m^2)n≥Ω(m2)), the value of the odd cycle game repeated in parallel n times is at least (1−1/4m2)O(n)(1-1/4m^2)^{O(n)}(1−1/4m2)O(n). Thus the following hold. 1. For parallel repetition of general games, the bounds of (1−ϵc)Ω(n/s)(1-\epsilon^c)^{\Omega(n/s)}(1−ϵc)Ω(n/s) given in [R. Raz, SIAM J. Comput., 27 (1998), pp. 763–803; T. Holenstein, in Proceedings of STOC 2002, ACM, New York, 2002, pp. 767–775] are of the right form, up to determining the exact value of the constant c≥2c\geq2c≥2. 2. For parallel repetition of XOR games, unique games, and projection games, the bounds of (1−ϵ2)Ω(n)(1-\epsilon^2)^{\Omega(n)}(1−ϵ2)Ω(n) given in [U. Feige, G. Kindler, and R. O'Donnell, in Proceedings of CCC 2007, IEEE Computer Society, Washington, DC, 2007, pp. 179–192] (for XOR games) and in [A. Rao, in Proceedings of STOC 2008, ACM, New York, 2008, pp. 1–10] (for unique and projection games) are tight. 3. For parallel repetition of the odd cycle game, the bound of 1−(1/m)⋅Ω~(n)1-(1/m)\cdot\tilde{\Omega}(\sqrt{n})1−(1/m)⋅Ω~(n​) given in [U. Feige, G. Kindler, and R. O'Donnell, in Proceedings of CCC 2007, IEEE Computer Society, Washington, DC, 2007, pp. 179–192] is almost tight. A major motivation for the recent interest in the strong parallel repetition problem is that a strong parallel repetition theorem would have implied that the unique game conjecture is equivalent to the NP hardness of distinguishing between instances of Max-Cut that are at least 1−ϵ21-\epsilon^21−ϵ2 satisfiable from instances that are at most 1−(2/π)⋅ϵ1-(2/\pi)\cdot\epsilon1−(2/π)⋅ϵ satisfiable. Our results suggest that this cannot be proved just by improving the known bounds on parallel repetition.