arXiv subjects

Rupak Majumdar

Publications and source records attributed to Rupak Majumdar.

114 records · Page 7Linked to original sources

arXiv2010

Discounting in Games across Time Scales

We introduce two-level discounted games played by two players on a perfect-information stochastic game graph. The upper level game is a discounted game and the lower level game is an undiscounted reachability game. Two-level games model hierarchical and sequential decision making under uncertainty across different time scales. We show the existence of pure memoryless optimal strategies for both players and an ordered field property for such games. We show that if there is only one player (Markov decision processes), then the values can be computed in polynomial time. It follows that whether the value of a player is equal to a given rational constant in two-level discounted games can be decided in NP intersected coNP. We also give an alternate strategy improvement algorithm to compute the value.

cs.LO↗

arXiv2010

Bounded Underapproximations

We show a new and constructive proof of the following language-theoretic result: for every context-free language L, there is a bounded context-free language L' included in L which has the same Parikh (commutative) image as L. Bounded languages, introduced by Ginsburg and Spanier, are subsets of regular languages of the form w1*w2*...wk* for some finite words w1,...,wk. In particular bounded subsets of context-free languages have nice structural and decidability properties. Our proof proceeds in two parts. First, using Newton's iterations on the language semiring, we construct a context-free subset Ls of L that can be represented as a sequence of substitutions on a linear language and has the same Parikh image as L. Second, we inductively construct a Parikh-equivalent bounded context-free subset of Ls. We show two applications of this result in model checking: to underapproximate the reachable state space of multithreaded procedural programs and to underapproximate the reachable state space of recursive counter programs. The bounded language constructed above provides a decidable underapproximation for the original problems. By iterating the construction, we get a semi-algorithm for the original problems that constructs a sequence of underapproximations such that no two underapproximations of the sequence can be compared. This provides a progress guarantee: every word w in L is in some underapproximation of the sequence. In addition, we show that our approach subsumes context-bounded reachability for multithreaded programs.

cs.LO↗

arXiv2008

Game Refinement Relations and Metrics

We consider two-player games played over finite state spaces for an infinite number of rounds. At each state, the players simultaneously choose moves; the moves determine a successor state. It is often advantageous for players to choose probability distributions over moves, rather than single moves. Given a goal, for example, reach a target state, the question of winning is thus a probabilistic one: what is the maximal probability of winning from a given state? On these game structures, two fundamental notions are those of equivalences and metrics. Given a set of winning conditions, two states are equivalent if the players can win the same games with the same probability from both states. Metrics provide a bound on the difference in the probabilities of winning across states, capturing a quantitative notion of state similarity. We introduce equivalences and metrics for two-player game structures, and we show that they characterize the difference in probability of winning games whose goals are expressed in the quantitative mu-calculus. The quantitative mu-calculus can express a large set of goals, including reachability, safety, and omega-regular properties. Thus, we claim that our relations and metrics provide the canonical extensions to games, of the classical notion of bisimulation for transition systems. We develop our results both for equivalences and metrics, which generalize bisimulation, and for asymmetrical versions, which generalize simulation.

cs.LO↗

arXiv2008

Stochastic Limit-Average Games are in EXPTIME

The value of a finite-state two-player zero-sum stochastic game with limit-average payoff can be approximated to within $ε$ in time exponential in a polynomial in the size of the game times polynomial in logarithmic in $\frac{1}ε$, for all $ε>0$.

cs.GT↗

arXiv2008

The Complexity of Coverage

We study the problem of generating a test sequence that achieves maximal coverage for a reactive system under test. We formulate the problem as a repeated game between the tester and the system, where the system state space is partitioned according to some coverage criterion and the objective of the tester is to maximize the set of partitions (or coverage goals) visited during the game. We show the complexity of the maximal coverage problem for non-deterministic systems is PSPACE-complete, but is NP-complete for deterministic systems. For the special case of non-deterministic systems with a re-initializing ``reset'' action, which represent running a new test input on a re-initialized system, we show that the complexity is again co-NP-complete. Our proof technique for reset games uses randomized testing strategies that circumvent the exponentially large memory requirement in the deterministic case.

cs.PL↗

arXiv2001

A Classification of Symbolic Transition Systems

We define five increasingly comprehensive classes of infinite-state systems, called STS1--5, whose state spaces have finitary structure. For four of these classes, we provide examples from hybrid systems.

cs.LO↗