The state-spaces needed to describe realistic physical embodied agents are extremely large, which presents a serious challenge to classical reinforcement learning schemes. In previous work (Jacob et al., 2005a, Jacob et al., 2005b) we introduced our EMBER (for EMbodiment-Based modulaR) reinforcement learning system, which describes a novel method for decomposing agents into modules based on the...

Our ongoing research in performance theory integrates methods for complex instrument parameter spaces and models for musical gestures. The latter are modelled as parametric curves residing in high-dimensional symbolic and physical gesture spaces. This article shortly exposes basic concepts of those spaces and the construction of symbolic gesture curves. It then discusses the problem of fitting ...

This paper presents a modeling method for a Mobile Modular Robot(MMR) which is composed of a mobile platform and a modular manipulator, the kinematics analysis is made for both the mobile platform and the upper manipulator. Then the dynamic equations are formulated considering the nonholonomic constraints and the controller is proposed with both the redundancy resolution and optimization of nul...

The aim of this paper is to provide a sound framework for addressing a difficult problem: the automatic construction of an autonomous agent’s modular architecture. We briefly present two apparently uncorrelated frameworks: Autonomous planning through Markov Decision Processes and Kernel Clustering. Our fundamental idea is that the former addresses autonomy whereas the latter allows to tackle se...

In his letter [Ser96], J.-P. Serre proves that the systems of Hecke eigenvalues given by modular forms (mod p) are the same as the ones given by locally constant functions A×B/B × → F̄p, where B is the endomorphism algebra of a supersingular elliptic curve. After giving a detailed exposition of Serre’s result, we prove that the systems of Hecke eigenvalues given by Siegel modular forms (mod p) o...

The properties of four elements (LPFE) and (UPFE), introduced by Isac and Persson, have been recently examined in Hilbert spaces, L-spaces and modular spaces. In this paper we prove a new theorem showing that a modular of form ρΦ(f) = R Ω Φ(t, |f(t)|) dμ(t) satisfies both (LPFE) and (UPFE) if and only if Φ is convex with respect to its second variable. A connection of this result with the study...

We describe an efficient procedure for proving stabilization of biological systems modeled as qualitative networks or genetic regulatory networks. For scalability, our procedure uses modular proof techniques, where state-space exploration is applied only locally to small pieces of the system rather than the entire system as a whole. Our procedure exploits the observation that, in practice, the ...

This paper considers the problem of modelling and forecasting for multivariate financial time series. The use of Dynamic Linear State Space models and Stochastic Volatility models with Kalman filtering techniques to address this problem is considered in the context of providing a modular software implementation. The combination of these two approaches is presented with an illustrative example. ...

Within the ITrackU project, a modular software architecture for model-based visual tracking and image understanding is being developed. The library is general-purpose with respect to object models, state-space parameters, visual modalities employed, number of cameras and targets, and tracking methodology. This provides the necessary building blocks for a seamless integration of a wide variety o...

Most existing modular model checking techniques betray their hardware roots: they assume that modules compose in parallel. In contrast, feature-oriented software designs, which have proven very successful in several domains, are sequential in the simplest case. Most interesting feature-oriented designs are really quasi-sequential compositions of parallel compositions. These designs demand and i...