Knowledge representation and reasoning for agro-ecological systems    

I have a master's degree in mathematics (Maths-Info) and am now a doctoral student working in Montpellier in the GraphIK team at Inria's LIRMM, in close collaboration with agronomists at Inra's UMR SYSTEM.
My computer science thesis is a continuation of my master's internship, supervised by the same research teams. I began the first stages of this subject by focusing on the representation of a winegrowing system.
The scientific objective of my thesis is the formal representation of the different elements of an agro-ecological system centered around the cultivation of perennial plants, and the interactions between these elements, so that this representation can be processed automatically by a machine. This automatic processing will rely on the semantics of the represented knowledge to answer various questions posed by agronomists.

• Starting date: Octobrer 2019
• University: MUSE University of Montpellier
• PhD school: I2S – Information, Structures, Systèmes
• Scientific field: IT
• Thesis management: Marie-Laure Mugnier (Université de Montpellier, LIRMM)
• Thesis supervisors: Christian Gary (Inrae, UMR AbSyS)
• Funding: #DigitAg – Inria
•  #DigitAg : Cofunded PhD – Axe 6 – Challenge 1

Keywords: Knowledge representation, agroecology, reasoning, information technology

Abstract: The scientific question addressed by this thesis is the following: how to formally represent complex systems such as agro-ecological systems, to allow an automatic exploitation of this representation based on its semantics? It is located in computer science in the field of knowledge representation and reasoning, a branch of artificial intelligence, which provides the theoretical and algorithmic foundations for the research to be carried out. This work has an interdisciplinary dimension and will be developed in close collaboration with agricultural researchers studying agro-ecological systems. Indeed, understanding agro-ecological systems poses challenges common to both disciplines: addressing the complexity of agro-ecological processes and their interactions, articulating several types and forms of knowledge, representing and managing dynamic and multi-scale processes. The results of the thesis will contribute to the creation of a tool (i) for eliciting, formalizing, integrating and sharing data and knowledge on the functioning and management of agroecosystems for the agro-ecological transition of agriculture, and (ii) offering various services based on the semantics of this data and knowledge, including: exploration and query based on domain ontologies, verification of the consistency of the modelling, analysis of the behaviour of the system and explanation of the inferences made, highlighting the consequences of system disturbances (in particular with a view to helping to formulate scientific hypotheses, for example, is the association of a certain type of plant with a crop likely to reduce the risk of pests and diseases?), the evaluation of technical change scenarios that meet specific objectives (e. g. reducing pest attacks). This thesis will be accompanied by projects in partnership with agricultural development organizations that will assess its products with a view to supporting farmers in an agro-ecological transition process.

Jury compound:

Rapporteurs :
- Jacques-Eric Bergez, Directeur de recherche, Inrae Toulouse, https://cv.archives ouvertes.fr/jacques-eric-bergez
- Fatiha Saïs, Professeur des Universités, Université Paris Saclay, https://www.lri.fr/~sais 

Examinateurs :
- Marianne Huchard, Professeur des Universités, UM
- Kamal Kansou, Chargé de recherche, Inrae Nantes, https://cv.archives-ouvertes.fr/kamal kansou

Direction de thèse :
- Marie-Laure Mugnier, Professeur des Universités, UM
- Christian Gary, Directeur de recherche, Inrae Montpellier

Invités :
- Jean-François Baget, Chargé de recherche Inria - co-encadrant
- Raphaël Métral, Ingénieur Inrae Montpellier - co-encadrant

Contact: elie.najm[AT]inria.fr​ – Tél: +33 4.67.41.85.85 / +33 (0)6.23.71.90.70