Let T1 and T2 be two countable strongly minimal theories with the DMP whose common theory is the theory of vector spaces over a fixed finite field. We show that T1 ∪ T2 has a strongly minimal completion.

Learning to perform complex tasks out of a sequence of simple small demonstrations is a key ability for more flexible robots. In this paper, we present a system that allows for the acquisition of such task executions based on dynamical movement primitives (DMPs). DMPs are a successful approach to encode and generalize robot movements. However, current applications involving DMPs mainly explore ...

The notion of equivalence that is typically used to relate Markovian process terms and to reduce their underlying state spaces is Markovian bisimilarity. The reason is that, besides being a congruence, Markovian bisimilarity is consistent with ordinary lumping, an exact aggregation for Markov chains. In this paper we show that two non-bisimulation-based Markovian behavioral equivalences – Marko...

The quantification of information leakage provides a quantitative evaluation of the security of a system. We propose the usage of Markovian processes to model deterministic and probabilistic systems. By using a methodology generalizing the lattice of information approach we model refined attackers capable to observe the internal behavior of the system, and quantify the information leakage of su...

We scrutinize the movie views from the Netflix website and find that there exist four particular temporal patterns. In particular some movies have multiple periods of view creation and destruction. Based on these observations we suggest that there exist stationary states in the human complex behavior. A model based on Markovian process is proposed to describe the dynamics of the movie watching ...

This paper extends and refines previous work on clustering of polarization-encoded images. The polarization-encoded images used in this work are considered as multidimensional parametric images where a clustering scheme based on Markovian Bayesian inference is applied. Hidden Markov Chains Model (HMCM) and Hidden Hierarchical Markovian Model (HHMM) show to handle effectively Mueller images and ...

The Hawkes process, which is generally defined for the continuous-time setting, can be described as a self-exciting simple point process with clustering effect, whose jump rate depends on its entire history. Due to past events determining future developments of processes, model not Markovian. In certain special circumstances, it Markovian generator if exciting function an exponential or sum fun...

In this paper we describe how an actor critic rein forcement learning agent in a non Markovian domain nds an optimal sequence of actions in a totally model free fashion that is the agent neither learns transitional probabilities and associated rewards nor by how much the state space should be augmented so that the Markov prop erty holds In particular we employ an Elman type re current neural ne...

The independent error model is often adopted to simplify the analysis of ARQ strategies. This assumption, however, is not true for channels where transmission errors occur in bursts. The limiting throughput efficiency of a class of continuous ARQ schemes with repeated transmissions is analysed under Markovian error patterns. The scheme without repeated transmissions, i.e. the classic go-back-N ...

This paper provides a performance evaluation of the TETRAPOL random access protocol. The results are based on a Markovian model which is also presented. The Markovian model is used to derive quality of service parameters, e.g. mean throughput, waiting probability, and mean random access delay. The analytical results are compared to results based on stochastic simulation. Our prototypic implemen...