AIAI Seminar - 13 November 2024 - Felipe Meneguzzi Title: Goal Recognition using Model Free Reinforcement Learning Summary: Goal Recognition aims to infer an agent's goal from a sequence of observations. While most existing approaches often rely on manually engineered domains and discrete representations, recent work has tried to obviate the need for such domains using machine learning. This talk covers recent methods we developed towards model free reinforcement learning applied to the problem of goal recognition. We proceed to discussing the interplay of such methods with agent architectures pointing to the future of research on machine learning and reasoning. Bio: Felipe Meneguzzi is Chair of Computing Science at the University of Aberdeen and Bridges Professor at the Pontifical Catholic University of Rio Grande do Sul (PUCRS). He received his PhD degree in Computer Science from King's College London (KCL) and holds an MSc degree from PUCRS. His career includes a decade as a Professor at PUCRS in Brazil, a Research Fellowship at Carnegie Mellon University (CMU) in the US and a brief stint in industry at Hewlett Packard. Felipe's research focuses on reasoning mechanisms for autonomous agents integrating symbolic and connectionist approaches to achieve efficient, explainable and socially good behaviour by following societal norms. To this end, Felipe has contributed with approaches involving planning, machine learning and logic spanning the width of modern AI research. Nov 13 2024 13.00 - 14.00 AIAI Seminar - 13 November 2024 - Felipe Meneguzzi AIAI Seminar hosted by Felipe Meneguzzi, Chair of Computing Science at the University of Aberdeen Dugald Stewart Building, room 3.10/3.11
AIAI Seminar - 13 November 2024 - Felipe Meneguzzi Title: Goal Recognition using Model Free Reinforcement Learning Summary: Goal Recognition aims to infer an agent's goal from a sequence of observations. While most existing approaches often rely on manually engineered domains and discrete representations, recent work has tried to obviate the need for such domains using machine learning. This talk covers recent methods we developed towards model free reinforcement learning applied to the problem of goal recognition. We proceed to discussing the interplay of such methods with agent architectures pointing to the future of research on machine learning and reasoning. Bio: Felipe Meneguzzi is Chair of Computing Science at the University of Aberdeen and Bridges Professor at the Pontifical Catholic University of Rio Grande do Sul (PUCRS). He received his PhD degree in Computer Science from King's College London (KCL) and holds an MSc degree from PUCRS. His career includes a decade as a Professor at PUCRS in Brazil, a Research Fellowship at Carnegie Mellon University (CMU) in the US and a brief stint in industry at Hewlett Packard. Felipe's research focuses on reasoning mechanisms for autonomous agents integrating symbolic and connectionist approaches to achieve efficient, explainable and socially good behaviour by following societal norms. To this end, Felipe has contributed with approaches involving planning, machine learning and logic spanning the width of modern AI research. Nov 13 2024 13.00 - 14.00 AIAI Seminar - 13 November 2024 - Felipe Meneguzzi AIAI Seminar hosted by Felipe Meneguzzi, Chair of Computing Science at the University of Aberdeen Dugald Stewart Building, room 3.10/3.11
Nov 13 2024 13.00 - 14.00 AIAI Seminar - 13 November 2024 - Felipe Meneguzzi AIAI Seminar hosted by Felipe Meneguzzi, Chair of Computing Science at the University of Aberdeen
