We consider Markov Decision Processes (MDPs) as transformers on probability distributions, where with respect to a scheduler that resolves nondeterminism, the MDP can be seen as ex...
Vijay Anand Korthikanti, Mahesh Viswanathan, Gul A...
Traditional architecture design approaches hide hardware uncertainties from the software stack through overdesign, which is often expensive in terms of power consumption. The recen...
Stochastic model checking has been used recently to assess, among others, dependability measures for a variety of systems. However, the employed numerical methods, as, e.g., suppor...
Abstract--Model checkers for concurrent probabilistic systems have become very popular within the last decade. The study of long-run average behavior has however received only scan...
We study Timed Branching Processes (TBPs), a natural extension of (multitype) Branching Processes (BPs) where each entity is equipped with a finite set of private continuous variab...
Adaptive techniques like voltage and frequency scaling, process variations and the randomness of input data contribute signi cantly to the statistical aspect of contemporary hardwa...
Discrete-Time Markov Chains (DTMCs) are a widely-used formalism to model probabilistic systems. On the one hand, available tools like PRISM or MRMC offer efficient model checking a...
Information hiding is a general concept which refers to the goal of preventing an adversary to infer secret information from the observables. Anonymity and Information Flow are exa...
Abstract--We introduce a stochastic extension of CCS endowed with structural operational semantics expressed in terms of measure theory. The set of processes is organised as a meas...