Analyse constructive

Résumé

L'analyse constructive est une branche des mathématiques constructives. Elle critique l'analyse mathématique classique et vise à fonder l'analyse sur des principes constructifs. Elle s'inscrit dans le courant de pensée constructiviste ou intuitionniste, dont les principaux membres ont été Kronecker, Brouwer ou Weyl. Critique de l'analyse classique La critique porte sur la façon dont est utilisée la notion d'existence, de disjonction et sur l'utilisation du raisonnement par l'absurde. L'analyse constructive peut être considérée comme apportant une précision sur les théorèmes classiques et leur démonstrations, en distinguant les énoncés considérés comme constructifs de ceux qui ne le sont pas. Ces derniers, classiquement vrais, demandent en analyse constructive à être prouvés d'une façon plus effective, ou bien à être remplacés par un énoncé constructif. Cette distinction entre énoncés constructifs et énoncés non constructifs ne manque pas d'intérêt par exemple dans la poss

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Human-Robot Interaction: Tackling the AI Challenges

Séverin Lemaignan

Human-Robot interaction is an area full of challenges for artificial intelligence: dynamic, partially unknown environments that are not originally designed for autonomous machines; a large variety of situations and objects to deal with, with possibly complex semantics; physical interactions with humans that requires fine, low-latency control, representation and management of several mental models, pertinent situation assessment skills...the list goes on. This article sheds light on some key decisional issues that are to be tackled for a cognitive robot to share space and tasks with a human, and present our take on these challenges. We adopt a constructive approach based on the identification and the effective implementation of individual and collaborative skills. These cognitive abilities cover geometric reasoning and situation assessment mainly based on perspective-taking and affordances, management and exploitation of each agent (human and robot) knowledge in separate cognitive models, natural multi-modal communication, "human-aware" task planning, and human and robot interleaved plan achievement. We present our design choices, the articulations between the diverse deliberative components of the robot, experimental results, and eventually discuss the strengths and weaknesses of our approach. It appears that explicit knowledge management, both symbolic and geometric, proves to be key as it pushes for a different, more semantic way to address the decision-making issue in human-robot interactions.

2014

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We present a constructive approach to the realization of a parallel system for the vision processing. This approach follows the classical software engineering principles: analysis, specification, design and implementation. The language CO-OPN (Concurrent Object Oriented Petri Net) is used to discribe the specification and the design of such system, while the implementation has been performed on a transputer machine. The writting of the CO-OPN specifications has been supported by the SANDS environement (Structured Algebraic Nets Development System) which also allow to simulate the behavior of the modelled system in an abstract way. A module, the main piece of the vision system, is presented that can be used for composing a computer vision architecture exploiting asynchronous data flows. This module is general enough to be duplicated and interconnected into a uniform graph. A module works by grouping asynchronous pieces of information coming through a channel, which delays them according to their relevance to the task of the module. The traditional separation between quantitative and symbolic processings vanishes since the module allows them to be implemented in a uniform way. The abstract specification of such principle is proposed, followed by a transformation refining this abstract specification into a concrete specification by introducing a distributed algorithm The concrete specification serves as the reference for the implementation on the distributed machine. We present a constructive approach to the realization of a parallel system for the vision processing. This approach follows the classical software engineering principles: analysis, specification, design and implementation. The language CO-OPN (Concurrent Object Oriented Petri Net) is used to discribe the specification and the design of such system, while the implementation has been performed on a transputer machine. The writting of the CO-OPN specifications has been supported by the SANDS environement (Structured Algebraic Nets Development System) which also allow to simulate the behavior of the modelled system in an abstract way. A module, the main piece of the vision system, is presented that can be used for composing a computer vision architecture exploiting asynchronous data flows. This module is general enough to be duplicated and interconnected into a uniform graph. A module works by grouping asynchronous pieces of information coming through a channel, which delays them according to their relevance to the task of the module. The traditional separation between quantitative and symbolic processings vanishes since the module allows them to be implemented in a uniform way. The abstract specification of such principle is proposed, followed by a transformation refining this abstract specification into a concrete specification by introducing a distributed algorithm The concrete specification serves as the reference for the implementation on the distributed machine.

1994

Chargement

Teaching Image-Processing Programming in Java

Daniel Sage, Michaël Unser

Image processing (IP) can be taught very effectively by complementing the basic lectures with computer laboratories where the participants can actively manipulate and process images. This offering can be made even more attractive by allowing the students to develop their own IP code within a reasonable time frame. After a brief review of existing software packages that can be used for teaching IP, we present a system that we have designed to be as “student-friendly” as possible. The software is built around ImageJ, a freely available, full-featured, and user-friendly program for image analysis. The computer sessions are alternated with lectures, typically, a three-hour session at the end of every chapter. The sessions are in the form of assignments that guide the students towards the solution of simple imaging problems. The starting point is typically the understanding and testing of some standard IP algorithm in Java. Next, students are asked to extend the algorithms progressively. This constructive approach is made possible thanks to a programmer-friendly environment and an additional software interface layer that greatly facilitates the developments of plug-ins for ImageJ. Taking into account the fact that our students are not experienced programmers (they typically do not even know Java), we use a “learn by example” teaching strategy, with good success.

IEEE2003

Chargement

1994