Abductive Reasoning with Minimal Sensing in a Home
il y a 4 semaines
**Abductive Reasoning with Minimal Sensing in a Home Environment**:
- Réf
- **ABG-111193**
- Sujet de Thèse- 16/02/2023- Financement public/privé- Mines Saint Etienne- Lieu de travail- Saint-Étienne - Auvergne-Rhône-Alpes - France- Intitulé du sujet- Abductive Reasoning with Minimal Sensing in a Home Environment- Champs scientifiques- Science de la donnée (stockage, sécurité, mesure, analyse)
- Informatique
- Mots clés- Semantic Web, Home Automation, Privacy, IoT, Logic, Neural Networks**Description du sujet**:
The domain of research of the thesis is knowledge representation and reasoning, a subfield of AI. Its objective is to evaluate abductive reasoning methods over sensor measurements performed in a home environment. Abductive reasoning in this context consists in finding logically sound hypotheses (e.g. ‘the dishwasher is on’) that explain observed sensor measurements (‘electric consumption has risen in the last two hours’) according to a model of human activity in a home.
The baseline assumption of the thesis is that only mínimal sensing is available in the home, as is the case in most homes today: smart meters provide aggregated values (every hour/day) but no information is available per room. Abductive reasoning is expected to help optimize home automation systems without relying on some ubiquitous sensing apparatus (which raises environmental, technical and privacy-preservation questions).
Several abduction mechanisms will be evaluated, including Abductive Logic Programming (for an exhaustive exploration of hypothesis space) and neural-symbolic integration methods (for a probabilistic exploration of hypothesis space)
**Prise de fonction**:
- 01/09/2023**Nature du financement**:
- Financement public/privé**Précisions sur le financement**:
- 50% ANR, 50% elm.leblanc**Présentation établissement et labo d'accueil**:
- Mines Saint EtienneThe position is located at Mines Saint-Étienne, with regular contact with R&D teams of elm.leblanc (Drancy) as well as researchers at IMT Nord Europe (Lille-Douai). The PhD student will be part of LIMOS (Laboratoire d’informatique, de modélisation et d’optimisation des systèmes), a research institution based in Saint-Étienne and Clermont-Ferrand. The thesis is supervised by Antoine Zimmermann (supervisor) and Victor Charpenay (co-supervisor), both associate professors at Mines Saint-Étienne.
**Site web**:
**Intitulé du doctorat**:
- Doctorat en informatique**Pays d'obtention du doctorat**:
- France**Etablissement délivrant le doctorat**:
- Ecole nationale supérieure des mines de Saint-Etienne**Ecole doctorale**:
- Sciences, ingénierie, santéHolder of a Master’s degree in computer science or data science. Prior knowledge in AI is expected, especially in computational logics, logic programming and/or Semantic Web technologies. Basic understanding of statistical inference methods and linear programming is also considered important. Technical skills required for the thesis include: multi-paradigm programming (Java, Lisp, R, Prolog,...), data modeling (UML, OWL, E/R, BPMN,...), Linux system administration (Bash, SSH, Docker,...).- 17/03/2023
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