BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Drupal iCal API//EN X-WR-CALNAME:Events items teaser X-WR-TIMEZONE:America/Toronto BEGIN:VTIMEZONE TZID:America/Toronto X-LIC-LOCATION:America/Toronto BEGIN:DAYLIGHT TZNAME:EDT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 DTSTART:20200308T070000 END:DAYLIGHT BEGIN:STANDARD TZNAME:EST TZOFFSETFROM:-0400 TZOFFSETTO:-0500 DTSTART:20191103T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:682b6fd92dc01 DTSTART;TZID=America/Toronto:20200415T110000 SEQUENCE:0 TRANSP:TRANSPARENT DTEND;TZID=America/Toronto:20200415T110000 URL:/computer-science/events/masters-thesis-presentatio n-ai-asking-for-help-with-cost-reinforcement-learning SUMMARY:Master’s Thesis Presentation • Artificial Intelligence — Aski ng\nfor Help with a Cost in Reinforcement Learning CLASS:PUBLIC DESCRIPTION:Summary \n\nPLEASE NOTE: THIS MASTER’S THESIS PRESENTATION WI LL BE GIVEN ONLINE.\n\nCOLIN VANDENHOF\, MASTER’S CANDIDATE\n_David R. Cheriton School of Computer Science_\n\nReinforcement learning (RL) is a p owerful tool for developing\nintelligent agents\, and the use of neural ne tworks makes RL techniques\nmore scalable to challenging real-world applic ations\, from\ntask-oriented dialogue systems to autonomous driving. Howev er\, one of\nthe major bottlenecks to the adoption of RL is efficiency\, a s it often\ntakes many time steps to learn an acceptable policy. \n DTSTAMP:20250519T175225Z END:VEVENT END:VCALENDAR