2,827 research outputs found
Decisive Markov Chains
We consider qualitative and quantitative verification problems for
infinite-state Markov chains. We call a Markov chain decisive w.r.t. a given
set of target states F if it almost certainly eventually reaches either F or a
state from which F can no longer be reached. While all finite Markov chains are
trivially decisive (for every set F), this also holds for many classes of
infinite Markov chains. Infinite Markov chains which contain a finite attractor
are decisive w.r.t. every set F. In particular, this holds for probabilistic
lossy channel systems (PLCS). Furthermore, all globally coarse Markov chains
are decisive. This class includes probabilistic vector addition systems (PVASS)
and probabilistic noisy Turing machines (PNTM). We consider both safety and
liveness problems for decisive Markov chains, i.e., the probabilities that a
given set of states F is eventually reached or reached infinitely often,
respectively. 1. We express the qualitative problems in abstract terms for
decisive Markov chains, and show an almost complete picture of its decidability
for PLCS, PVASS and PNTM. 2. We also show that the path enumeration algorithm
of Iyer and Narasimha terminates for decisive Markov chains and can thus be
used to solve the approximate quantitative safety problem. A modified variant
of this algorithm solves the approximate quantitative liveness problem. 3.
Finally, we show that the exact probability of (repeatedly) reaching F cannot
be effectively expressed (in a uniform way) in Tarski-algebra for either PLCS,
PVASS or (P)NTM.Comment: 32 pages, 0 figure
A Metric for Linear Temporal Logic
We propose a measure and a metric on the sets of infinite traces generated by
a set of atomic propositions. To compute these quantities, we first map
properties to subsets of the real numbers and then take the Lebesgue measure of
the resulting sets. We analyze how this measure is computed for Linear Temporal
Logic (LTL) formulas. An implementation for computing the measure of bounded
LTL properties is provided and explained. This implementation leverages SAT
model counting and effects independence checks on subexpressions to compute the
measure and metric compositionally
An Application of Quantum Finite Automata to Interactive Proof Systems
Quantum finite automata have been studied intensively since their
introduction in late 1990s as a natural model of a quantum computer with
finite-dimensional quantum memory space. This paper seeks their direct
application to interactive proof systems in which a mighty quantum prover
communicates with a quantum-automaton verifier through a common communication
cell. Our quantum interactive proof systems are juxtaposed to
Dwork-Stockmeyer's classical interactive proof systems whose verifiers are
two-way probabilistic automata. We demonstrate strengths and weaknesses of our
systems and further study how various restrictions on the behaviors of
quantum-automaton verifiers affect the power of quantum interactive proof
systems.Comment: This is an extended version of the conference paper in the
Proceedings of the 9th International Conference on Implementation and
Application of Automata, Lecture Notes in Computer Science, Springer-Verlag,
Kingston, Canada, July 22-24, 200
Endogenous Social Preferences, Heterogeneity and Cooperation
We set up an analytical framework focusing on the problem of interaction over time when economic agents are characterized by various types of distributional social preferences. We develop an evolutionary approach in which individual preferences are endogenous and account for the evolution of cooperation when all the players are initially entirely selfish. In particular, within motivationally heterogeneous agents embedded in a social network, we adopt a variant of the indirect evolutionary approach, where material payoffs play a critical role, and assume that a coevolutionary process occurs in which subjective preferences gradually evolve due to a key mechanism involving behavioral choices, relational intensity and degree of social openness. The simulations we carried out led to strongly consistent results with regard to the evolution of player types, the dynamics of material payoffs, the creation of significant interpersonal relationships among agents and the frequency of cooperation. In the long run, cooperation turns out to be the strategic choice that obtains the best performances, in terms of material payoffs, and "nice guys", far from finishing last, succeed in coming out ahead.Behavioral Economics; Cooperation; Prisoner's Dilemma; Social Evolution; Heterogeneous Social Preferences; Indirect Evolutionary Approach
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