Reference number : GC-2017-Q1-03206, amendment number : , agreement type : G, recipient legal name : Kabanza, Froduald (Université de Sherbrooke), recipient country : CA, recipient province : nan, recipient city : Quebec|Québec, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : 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., program purpose french : 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., agreement title english : Advanced Algorithms for Plan Recognition, agreement title french : Advanced Algorithms for Plan Recognition, agreement number : RGPIN, agreement value : 170000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada