Performance evaluation of computer software or hardware architectures may rely on the analysis of a complex stochastic model whose specification is usually given in terms of a high level formalism such as queueing networks, stochastic Petri nets, stochastic automata or Markovian process algebras. Compositionality is a key-feature of many of these formalisms and allows the modeller to combine se...

Probabilistic hybrid discrete/continuous models, such as Concurrent Probabilistic Hybrid Automata (CPHA) are convenient tools for modeling complex robotic systems. In this paper, we present a novel method for estimating the hybrid state of CPHA that achieves robustness by balancing greedy and stochastic search. To accomplish this, we 1) develop an efficient stochastic sampling approach for CPHA...

Cellular automata provide an interesting concept for modelling and simulation. Besides advanced modelling approaches like the Lattice Boltzmann Method cellular automata are also used for simulation in population dynamics, reaction diffusion systems or bio-medicine. While the basic concepts of cellular automata are rather clear and unambiguous, there exists no general mathematical formalism as t...

In this article, we recall different approaches to the constraint-based, symbolic analysis of hybrid discrete-continuous systems and combine them to a technology able to address hybrid systems exhibiting both non-deterministic and probabilistic behavior akin to infinite-state Markov decision processes. To enable mechanized analysis of such systems, we extend the reasoning power of arithmetic sa...

An intelligent controller is described for an automated vehicle planning its trajectory based on sensor and communication data received. The intelligent controller is designed using a stochastic learning automaton. Using the data received from on-board sensors, two automata (for lateral and longitudinal actions) are capable of learning the best possible actions to avoid collisions. The system h...

The main topic of this study is the modelling and verification of biological systems using ω-automata. This work focuses on the protein folding problem and the infinite behaviour it features in many cases. Specifically, stochastic computational models with infinite input are used in this paper’s approach and indicative aspects of a biological problem are presented using both ω-automata and prob...

Please cite this article in press as: J. Akbari Tork learning automata approach, Comput. Commun During the last decades, many studies have been conducted on multicast routing in mobile ad hoc networks (MANET) and a host of algorithms have been proposed. In existing algorithms, the mobility characteristics are assumed to be constant, and so they do not scale well when the mobility parameters are...