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NonDeterministic Exponential Time has TwoProver Interactive Protocols
"... We determine the exact power of twoprover interactive proof systems introduced by BenOr, Goldwasser, Kilian, and Wigderson (1988). In this system, two allpowerful noncommunicating provers convince a randomizing polynomial time verifier in polynomial time that the input z belongs to the language ..."
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Cited by 402 (40 self)
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We determine the exact power of twoprover interactive proof systems introduced by BenOr, Goldwasser, Kilian, and Wigderson (1988). In this system, two allpowerful noncommunicating provers convince a randomizing polynomial time verifier in polynomial time that the input z belongs to the language L. It was previously suspected (and proved in a relativized sense) that coNPcomplete languages do not admit such proof systems. In sharp contrast, we show that the class of languages having twoprover interactive proof systems is nondeterministic exponential time. After the recent results that all languages in PSPACE have single prover interactive proofs (Lund, Fortnow, Karloff, Nisan, and Shamir), this represents a further step demonstrating the unexpectedly immense power of randomization and interaction in efficient provability. Indeed, it follows that multiple provers with coins are strictly stronger than without, since NEXP # NP. In particular, for the first time, provably polynomial time intractable languages turn out to admit “efficient proof systems’’ since NEXP # P. We show that to prove membership in languages in EXP, the honest provers need the power of EXP only. A consequence, linking more standard concepts of structural complexity, states that if EX P has polynomial size circuits then EXP = Cg = MA. The first part of the proof of the main result extends recent techniques of polynomial extrapolation of truth values used in the single prover case. The second part is a verification scheme for multilinearity of an nvariable function held by an oracle and can be viewed as an independent result on program verification. Its proof rests on combinatorial techniques including the estimation of the expansion rate of a graph.
Using Autoreducibility to Separate Complexity Classes
 In Proceedings of the 36th IEEE Symposium on Foundations of Computer Science
, 1995
"... A language is autoreducible if it can be reduced to itself by a Turing machine that does not ask its own input to the oracle. We use autoreducibility to separate exponential space from doubly exponential space by showing that all Turingcomplete sets for exponential space are autoreducible but there ..."
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Cited by 23 (11 self)
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A language is autoreducible if it can be reduced to itself by a Turing machine that does not ask its own input to the oracle. We use autoreducibility to separate exponential space from doubly exponential space by showing that all Turingcomplete sets for exponential space are autoreducible but there exists some Turingcomplete set for doubly exponential space that is not. We immediately also get a separation of logarithmic space from polynomial space. Although we already know how to separate these classes using diagonalization, our proofs separate classes solely by showing they have different structural properties, thus applying Post's Program to complexity theory. We feel such techniques may prove unknown separations in the future. In particular if we could settle the question as to whether all complete sets for doubly exponential time were autoreducible we would separate polynomial time from either logarithmic space or polynomial space. We also show several other theorems about autore...
Email and the unexpected power of interaction
 Structure in Complexity theory
, 1988
"... This is a true fable about Merlin, the infinitely intelligent but never trusted magician; and Arthur, the reasonable but impatient sovereign with an occasional unorthodox request; about the concept of an efficient proof; about polynomials and interpolation, electronic mail, coin flipping, and the in ..."
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Cited by 18 (3 self)
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This is a true fable about Merlin, the infinitely intelligent but never trusted magician; and Arthur, the reasonable but impatient sovereign with an occasional unorthodox request; about the concept of an efficient proof; about polynomials and interpolation, electronic mail, coin flipping, and the incredible power of interaction. About MIP, IP, #P, P SP ACE, NEXP T IME, and new techniques that do not relativize. About fast progress, fierce competition, and email ethics. 1 How did Merlin end up in the cave? In the court of King Arthur1 there lived 150 knights and 150 ladies. “Why not 150 married couples, ” the King contemplated one rainy afternoon, and action followed the thought. He asked the Royal Secret Agent (RSA) to draw up a diagram with all the 300 names, indicating bonds of mutual interest between lady and knight by a red line; and the lack thereof, by a blue line. The diagram, with its 1502 = 22, 500 colored lines, looked somewhat confusing, yet it should not confuse Merlin, the court magician, to whom it was subsequently presented by Arthur with the express order to find a perfect matching consisting exclusively of red lines. Merlin walked away, looked at the diagram, and, with his unlimited intellectual ability, immediately recognized that none of the 150! possibilities gave an allred perfect matching. He quickly completed the 150! diagrams, highlighting the wrong blue line in
Relativizing versus nonrelativizing techniques: The role of local checkability
 UNIVERSITY OF CALIFORNIA, BERKELEY
, 1992
"... Contradictory oracle results have traditionally been interpreted as giving some evidence that resolving a complexity issue is difficult. However, for quite a while, there have been a few known complexity results that do not hold for every oracle, at least in the most obvious way of relativizing the ..."
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Cited by 11 (1 self)
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Contradictory oracle results have traditionally been interpreted as giving some evidence that resolving a complexity issue is difficult. However, for quite a while, there have been a few known complexity results that do not hold for every oracle, at least in the most obvious way of relativizing the results. In the early 1990’s, a sequence of important nonrelativizing results concerning “noncontroversially relativizable ” complexity classes has been proved, mainly using algebraic techniques. Although the techniques used to obtain these results seem similar in flavor, it is not clear what common features of complexity they are exploiting. It is also not clear to what extent oracle results should be trusted as a guide to estimating the difficulty of proving complexity statements, in light of these nonrelativizing techniques. The results in this paper are intended to shed some light on these issues. First, we give a list of simple axioms based on Cobham’s machineless characterization of P [Cob64]. We show that a complexity statement (provably) holds relative to all oracles if and only if it is a consequence of these axioms. Thus, these axioms in some sense capture the set of techniques that relativize. Oracle results, while not necessarily showing that resolving a complexity conjecture is “beyond current technology” at least show that the result is
The Power Of Interaction
, 1991
"... : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : vii Chapter 1. INTRODUCTION : : : : : : : : : : : : : : : : : : : : : : : : : 1 2. PRELIMINARIES : : : : : : : : : : : : : : : : : : : : : : : : : 4 2.1 Basic Definitions : : : : : : : : : : : : : : : : : : : : : : : 4 2.1.1 Basics : : ..."
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Cited by 10 (0 self)
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: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : vii Chapter 1. INTRODUCTION : : : : : : : : : : : : : : : : : : : : : : : : : 1 2. PRELIMINARIES : : : : : : : : : : : : : : : : : : : : : : : : : 4 2.1 Basic Definitions : : : : : : : : : : : : : : : : : : : : : : : 4 2.1.1 Basics : : : : : : : : : : : : : : : : : : : : : : : : 4 2.1.2 Boolean Formulas : : : : : : : : : : : : : : : : : 4 2.1.3 Arithmetic Formulas and Expressions : : : : : : 5 2.2 Computational Models : : : : : : : : : : : : : : : : : : : : 9 2.2.1 Deterministic Computation : : : : : : : : : : : : 9 2.2.2 Probabilistic Computation : : : : : : : : : : : : 11 2.2.3 NonDeterministic Computation : : : : : : : : : 12 2.2.4 Alternating Computations : : : : : : : : : : : : 13 2.2.5 Interactive Proof Systems : : : : : : : : : : : : : 13 2.2.6 Multiple Prover Interactive Proof Systems : : : 15 2.2.7 Computation relative to an Oracle : : : : : : : : 15 2.3 Complexity Classes : : : : : : : : : : : : : : : : : : : : ...
Probabilistic Type2 Operators and "Almost"Classes
 Electronic Colloquium on Computational Complexity
, 1998
"... We define and examine several probabilistic operators ranging over sets (i.e., operators of type 2), among them the formerly studied ALMOSToperator. We compare their power and prove that they all coincide for a wide variety of classes. As a consequence, we characterize the ALMOSToperator which ran ..."
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We define and examine several probabilistic operators ranging over sets (i.e., operators of type 2), among them the formerly studied ALMOSToperator. We compare their power and prove that they all coincide for a wide variety of classes. As a consequence, we characterize the ALMOSToperator which ranges over infinite objects (sets) by a boundederror probabilistic operator which ranges over strings, i.e. finite objects. This leads to a number of consequences about complexity classes of current interest. As applications, we obtain (a) a criterion for measure 1 inclusions of complexity classes, (b) a criterion for inclusions of complexity classes relative to a random oracle, (c) a new upper time bound for ALMOSTPSPACE, and (d) a characterization of ALMOSTPSPACE in terms of checking stack automata. Finally, a connection between the power of ALMOSTPSPACE and that of probabilistic NC 1 circuits is given. 1 Introduction In a fundamental paper, John Gill introduced probabilistic Turing m...