Searching for Cost-Optimized Strategies: An Agricultural Application

Christine Largouët (1, 2, 3) , Yulong Zhao (3, 4) , Marie-Odile Cordier (3, 4, 1)

1 LACODAM - Large Scale Collaborative Data Mining
2 AGROCAMPUS OUEST
3 IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires
4 UR - Université de Rennes

We consider a system modeled as a set of interacting components evolving along time according to explicit timing constraints. The decision making problem consists in selecting and organizing actions in order to reach a goal state in a limited time and in an optimal manner, assuming actions have a cost. We propose to reformulate the planning problem in terms of model-checking and controller synthesis such that the state to reach is expressed using a temporal logic. We have chosen to represent each agent using the formalism of Priced Timed Game Au-tomata (PTGA) and a set of knowledge. PTGA is an extension of Timed Automata that allows the representation of cost on actions and the definition of a goal (to reach or to avoid). This paper describes two algorithms designed to answer the planning problem on a network of agents and proposes practical implementation using model-checking tools that shows promising results on an agricultural application: a grassland based dairy production system.

Mots clés: Decision Support System; Temporal Planning; Optimized Planning; Timed Automata; Model-checking

Domaines: Intelligence artificielle [cs.AI]

Christine Largouët, Yulong Zhao, Marie-Odile Cordier. Searching for Cost-Optimized Strategies: An Agricultural Application. 2nd International Conference, ICDSST 2016, May 2016, Plymouth, United Kingdom. pp.31 - 43, ⟨10.1007/978-3-319-32877-5_3⟩. ⟨hal-01398660⟩