In this paper we consider the problem of finding a decomposed solution to a Markov model where the action rates may depend on the global state space. To do this we consider regular cycles in the underlying state space and show that a semi-product form solution exists when the functions describing the action rates have specific forms. The approach is illustrated with a simple queueing example al...

Robotic manipulation of deformable objects is a difficult problem especially because of the complexity of the many different ways an object can deform. Searching such a high dimensional state space makes it difficult to recognize, track, and manipulate deformable objects. In this paper, we introduce a predictive, model-driven approach to address this challenge, using a pre-computed, simulated d...

We consider the optimal stopping problem of a Markov process {xt : t ≥ 0} when the controller is allowed to stop only at the arrival times of a signal, that is, at a sequence of instants {τn : n ≥ 1} independent of {xt : t ≥ 0}. We solve in detail this problem for general Markov– Feller processes with compact state space when the interarrival times of the signal are independent identically dist...

Here we prove Lemma 3 from the paper Instantiation Reduction in Iterative Parameterised Three-Valued Model Checking submitted to SBMF 2015. According to our parameterisation rules defined in [1], the application of parameterisation (and parameter instantiation) only affects the values of transitions an labellings but not the state space. Thus, M (Bn) and M (Bn)(Bm) in Lemma 3 are both defined o...

We analyze finite sample properties of the quasi-maximum likelihood estimators of longmemory stochastic volatility models. The estimates are done in the time domain using autoregressive and moving average in the state space representation. The results are compared with usual estimators of the long-memory parameter.

This paper introduces decision-theoretic planning techniques into automatic music generation. Markov decision processes (MDPs) are a mathematical model of planning under uncertainty, and factored MDPs demonstrate great advantages in an environment where the state space is large. Given a melody, we use a factored MDP planner to fill in the other three voices, based on the characteristics of clas...

Net unfoldings have attracted much attention as a powerful technique for combating state space explosion in model checking. The method has been applied to veriication of 1-safe ((nite) Petri nets, and more recently also to other classes of nite-state systems such as synchronous products of nite transition systems. We show how unfoldings can be extended to the context of innnite-state systems. M...

The state space explosion problem is a hurdle in the acceptance of model checking as a viable tool for verification of large-scale designs. Abstractions may be used to simplify designs, while preserving target verification properties. We propose a simple methodology for abstracting away portions of the data path, thus rendering a large state-space model of the design amenable for verification u...

Model-based tutoring systems are driven by an abstract domain model and solver that is used for solution validation and student guidance. Such models are robust but costly to produce and are not always adaptive to specific students’ needs. Data-driven methods such as the Hint Factory are comparatively cheaper and can be used to generate individualized hints without a complete domain model. In t...

This article presents the results of the Model Checking Contest held at Petri Nets 2012 in Hambourg. This contest aimed at a fair and experimental evaluation of the performances of model checking techniques applied to Petri nets. This is the second edition after a successful one in 2011 [29]. The participating tools were compared on several examinations (state space generation and evaluation of...