[PhD’s Corner] Elie Najm: Knowledge representation and reasoning for agro-ecological systems

Elie Najm is one of the #DigitAg co-funded PhDs

Knowledge representation and reasoning for agro-ecological systems 

  • Start Date: 1 october 2019
  • University:  MUSE University of Montpellier
  • PhD School: 166 – I2S – Information, Structures, Systèmes
  • Field(s): Computer science
  • Doctoral Thesis Advisor: Marie-Laure Mugnier (Université de Montpellier, LIRMM)
  • Co-supervisors : Christian Gary (Inra, System)
  • Funding: #DigitAg & Inria
  • #DigitAg: Axis 6, Challenge 1

Keywords: Knowledge representation, agroecology, reasoning, computer science

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.



Contact:  elie.najm [AT] inria.fr  – Cell: +33 (0)623719070

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