Subventions et des contributions :

Titre :
Advanced Algorithms for Plan Recognition
Numéro de l’entente :
RGPIN
Valeur d'entente :
170 000,00 $
Date d'entente :
10 mai 2017 -
Organisation :
Conseil de recherches en sciences naturelles et en génie du Canada
Location :
Québec, Autre, CA
Numéro de référence :
GC-2017-Q1-03206
Type d'entente :
subvention
Type de rapport :
Subventions et des contributions
Renseignements supplémentaires :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023)

Nom légal du bénéficiaire :
Kabanza, Froduald (Université de Sherbrooke)
Programme :
Programme de subventions à la découverte - individuelles
But du programme :

Artificial intelligence (AI) presents the potential to profoundly transform our society with various applications that will positively affect the economy and our everyday life. Intelligent automated agents will soon be driving applications in many including, transportation, social media, game AI, educational tools, intelligence analysis, defense and security. The ability of these agents to effectively support and naturally interact with people will largely depend on their proficiency to recognize the goals and plans of other agents. The problem of recognizing the goals or plans of other agents is known as the plan recognition problem or the intent recognition problem. While interesting advances have been made over the years, today plan recognition algorithms are too ineffective for many applications. The objective of this research program is to explore, improve, and develop plan recognition algorithms that can cope with complex applications. The research avenues articulate around automated planning, algorithmic game-theory and machine learning.