Alexis Brenon

Alexis Brenon
  • Master of Science
  • PhD Student at Grenoble Computer Science Laboratory

About

10
Publications
881
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
50
Citations
Current institution
Grenoble Computer Science Laboratory
Current position
  • PhD Student

Publications

Publications (10)
Preprint
In a voice-controlled smart-home, a controller must respond not only to user's requests but also according to the interaction context. This paper describes Arcades, a system which uses deep reinforcement learning to extract context from a graphical representation of home automation system and to update continuously its behavior to the user's one. T...
Article
Full-text available
In a voice-controlled smart-home, a controller must respond not only to user's requests but also according to the interaction context. This paper describes Arcades, a system which uses deep reinforcement learning to extract context from a graphical representation of home automation system and to update continuously its behavior to the user's one. T...
Thesis
Full-text available
Les habitats intelligents, résultants de la convergence de la domotique, de l'informatique ubiquitaire et de l'intelligence artificielle, assistent leurs habitants dans les situations du quotidien pour améliorer leur qualité de vie.En permettant aux personnes dépendantes et âgées de rester à domicile plus longtemps, ces habitats permettent de fourn...
Conference Paper
Full-text available
In smart homes, prediction and decision are often defined a priori and require tuning from the user, which can be tedious, and complex. However, these smart homes have the ability to analyze the user's behavior so as to adapt their decisions automatically. We present a preliminary study that tests a voice based decision system in the home, which is...
Conference Paper
Full-text available
Dans les habitats intelligents, les prédictions et décisions qui sont souvent faites a priori nécessitent de la part de l'utilisateur une configuration qui peut être complexe et fastidieuse. Ces habitats ont pourtant des capacités de perception requises pour analyser le comportement de l'uti-lisateur et modifier ses décisions automatiquement. Nous...
Conference Paper
Full-text available
This paper presents the use of a model which mixes logical knowledge and statistical inference to recognize Activities of Daily Living (ADL) from sensors in a smart home. This model called Markov Logic Network (MLN) has different implementations and we propose to compare three of them, from the widely used Alchemy to the new generic framework DeepD...

Network

Cited By