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78
Probabilistic checking of proofs: a new characterization of NP
- JOURNAL OF THE ACM
, 1998
"... We give a new characterization of NP: the class NP contains exactly those languages L for which membership proofs (a proof that an input x is in L) can be verified probabilistically in polynomial time using logarithmic number of random bits and by reading sublogarithmic number of bits from the proof ..."
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Cited by 414 (26 self)
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We give a new characterization of NP: the class NP contains exactly those languages L for which membership proofs (a proof that an input x is in L) can be verified probabilistically in polynomial time using logarithmic number of random bits and by reading sublogarithmic number of bits from the proof. We discuss implications of this characterization; specifically, we show that approximating Clique and Independent Set, even in a very weak sense, is NP-hard.
A Survey of Computational Complexity Results in Systems and Control
, 2000
"... The purpose of this paper is twofold: (a) to provide a tutorial introduction to some key concepts from the theory of computational complexity, highlighting their relevance to systems and control theory, and (b) to survey the relatively recent research activity lying at the interface between these fi ..."
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Cited by 187 (18 self)
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The purpose of this paper is twofold: (a) to provide a tutorial introduction to some key concepts from the theory of computational complexity, highlighting their relevance to systems and control theory, and (b) to survey the relatively recent research activity lying at the interface between these fields. We begin with a brief introduction to models of computation, the concepts of undecidability, polynomial time algorithms, NP-completeness, and the implications of intractability results. We then survey a number of problems that arise in systems and control theory, some of them classical, some of them related to current research. We discuss them from the point of view of computational complexity and also point out many open problems. In particular, we consider problems related to stability or stabilizability of linear systems with parametric uncertainty, robust control, time-varying linear systems, nonlinear and hybrid systems, and stochastic optimal control.
Interactive proofs and the hardness of approximating cliques
- JOURNAL OF THE ACM
, 1996
"... The contribution of this paper is two-fold. First, a connection is shown between approximating the size of the largest clique in a graph and multi-prover interactive proofs. Second, an efficient multi-prover interactive proof for NP languages is constructed, where the verifier uses very few random b ..."
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Cited by 170 (11 self)
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The contribution of this paper is two-fold. First, a connection is shown between approximating the size of the largest clique in a graph and multi-prover interactive proofs. Second, an efficient multi-prover interactive proof for NP languages is constructed, where the verifier uses very few random bits and communication bits. Last, the connection between cliques and efficient multiprover interactive proofs, is shown to yield hardness results on the complexity of approximating the size of the largest clique in a graph. Of independent interest is our proof of correctness for the multilinearity test of functions.
Delegating computation: interactive proofs for muggles
- In Proceedings of the ACM Symposium on the Theory of Computing (STOC
, 2008
"... In this work we study interactive proofs for tractable languages. The (honest) prover should be efficient and run in polynomial time, or in other words a “muggle”. 1 The verifier should be super-efficient and run in nearly-linear time. These proof systems can be used for delegating computation: a se ..."
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Cited by 113 (6 self)
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In this work we study interactive proofs for tractable languages. The (honest) prover should be efficient and run in polynomial time, or in other words a “muggle”. 1 The verifier should be super-efficient and run in nearly-linear time. These proof systems can be used for delegating computation: a server can run a computation for a client and interactively prove the correctness of the result. The client can verify the result’s correctness in nearly-linear time (instead of running the entire computation itself). Previously, related questions were considered in the Holographic Proof setting by Babai, Fortnow, Levin and Szegedy, in the argument setting under computational assumptions by Kilian, and in the random oracle model by Micali. Our focus, however, is on the original interactive proof model where no assumptions are made on the computational power or adaptiveness of dishonest provers. Our main technical theorem gives a public coin interactive proof for any language computable by a log-space uniform boolean circuit with depth d and input length n. The verifier runs in time (n+d)·polylog(n) and space O(log(n)), the communication complexity is d · polylog(n), and the prover runs in time poly(n). In particular, for languages computable by log-space uniform N C (circuits of polylog(n) depth), the prover is efficient, the verifier runs in time n · polylog(n) and space O(log(n)), and the communication complexity is polylog(n).
On the undecidability of probabilistic planning and infinite-horizon partially observable Markov decision process problems
- Artificial Intelligence
"... Abstract We investigate the computability of problems in probabilistic planning and partially observable infinite-horizon Markov decision processes. The undecidability of the string-existence problem for probabilistic finite automata is adapted to show that the following problem of plan existence i ..."
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Cited by 103 (0 self)
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Abstract We investigate the computability of problems in probabilistic planning and partially observable infinite-horizon Markov decision processes. The undecidability of the string-existence problem for probabilistic finite automata is adapted to show that the following problem of plan existence in probabilistic planning is undecidable: given a probabilistic planning problem, determine whether there exists a plan with success probability exceeding a desirable threshold. Analogous policy-existence problems for partially observable infinite-horizon Markov decision processes under discounted and undiscounted total reward models, average-reward models, and state-avoidance models are all shown to be undecidable. The results apply to corresponding approximation problems as well.
On the Undecidability of Probabilistic Planning and Related Stochastic Optimization Problems
- Artificial Intelligence
, 2003
"... Automated planning, the problem of how an agent achieves a goal given a repertoire of actions, is one of the foundational and most widely studied problems in the AI literature. The original formulation of the problem makes strong assumptions regarding the agent's knowledge and control over the ..."
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Cited by 74 (0 self)
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Automated planning, the problem of how an agent achieves a goal given a repertoire of actions, is one of the foundational and most widely studied problems in the AI literature. The original formulation of the problem makes strong assumptions regarding the agent's knowledge and control over the world, namely that its information is complete and correct, and that the results of its actions are deterministic and known.
The Boundedness of All Products of a Pair of Matrices is Undecidable
, 2000
"... We show that the boundedness of the set of all products of a given pair Sigma of rational matrices is undecidable. Furthermore, we show that the joint (or generalized) spectral radius #(#) is not computable because testing whether #(#)61 is an undecidable problem. As a consequence, the robust stabil ..."
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Cited by 68 (13 self)
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We show that the boundedness of the set of all products of a given pair Sigma of rational matrices is undecidable. Furthermore, we show that the joint (or generalized) spectral radius #(#) is not computable because testing whether #(#)61 is an undecidable problem. As a consequence, the robust stability of linear systems under time-varying perturbations is undecidable, and the same is true for the stability of a simple class of hybrid systems. We also discuss some connections with the so-called "finiteness conjecture". Our results are based on a simple reduction from the emptiness problem for probabilistic finite automata, which is known to be undecidable.
Recursive Markov decision processes and recursive stochastic games
- In Proc. of 32nd Int. Coll. on Automata, Languages, and Programming (ICALP’05
, 2005
"... Abstract. We introduce Recursive Markov Decision Processes (RMDPs) and Recursive Simple Stochastic Games (RSSGs), and study the decidability and complexity of algorithms for their analysis and verification. These models extend Recursive Markov Chains (RMCs), introduced in [EY05a,EY05b] as a natural ..."
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Cited by 52 (11 self)
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Abstract. We introduce Recursive Markov Decision Processes (RMDPs) and Recursive Simple Stochastic Games (RSSGs), and study the decidability and complexity of algorithms for their analysis and verification. These models extend Recursive Markov Chains (RMCs), introduced in [EY05a,EY05b] as a natural model for verification of probabilistic procedural programs and related systems involving both recursion and probabilistic behavior. RMCs define a class of denumerable Markov chains with a rich theory generalizing that of stochastic context-free grammars and multi-type branching processes, and they are also intimately related to probabilistic pushdown systems. RMDPs & RSSGs extend RMCs with one controller or two adversarial players, respectively. Such extensions are useful for modeling nondeterministic and concurrent behavior, as well as modeling a system’s interactions with an environment. We provide a number of upper and lower bounds for deciding, given an RMDP (or RSSG) A and probability p, whether player 1 has a strategy to force termination at a desired exit with probability at least p. We also address “qualitative ” termination questions, where p = 1, and model checking questions. 1
Complexity of Planning with Partial Observability
- ICAPS 2004. Proceedings of the Fourteenth International Conference on Automated Planning and Scheduling
, 2004
"... We show that for conditional planning with partial observability the problem of testing existence of plans with success probability 1 is 2-EXP-complete. This result completes the complexity picture for non-probabilistic propositional planning. We also give new proofs for the EXP-hardness of conditio ..."
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Cited by 51 (3 self)
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We show that for conditional planning with partial observability the problem of testing existence of plans with success probability 1 is 2-EXP-complete. This result completes the complexity picture for non-probabilistic propositional planning. We also give new proofs for the EXP-hardness of conditional planning with full observability and the EXPSPACE-hardness of conditional planning without observability. The proofs demonstrate how lack of full observability allows the encoding of exponential space Turing machines in the planning problem, and how the necessity to have branching in plans corresponds to the move to a complexity class defined in terms of alternation from the corresponding deterministic complexity class. Lack of full observability necessitates the use of beliefs states, the number of which is exponential in the number of states, and alternation corresponds to the choices a branching plan can make.
Undecidable Problems for Probabilistic Automata of Fixed Dimension
- Theory of Computing Systems
, 2001
"... We prove that several problems associated to probabilistic finite automata are undecidable for automata whose number of input letters and number of states are fixed. As a corollary of one of our results we prove that the problem of determining if the set of all products of two 47 × 47 matr ..."
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Cited by 43 (3 self)
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We prove that several problems associated to probabilistic finite automata are undecidable for automata whose number of input letters and number of states are fixed. As a corollary of one of our results we prove that the problem of determining if the set of all products of two 47 × 47 matrices with nonnegative rational entries is bounded is undecidable.
