By Sudeep Dasari
This post is cross-listed at the SAIL Blog and the CMU ML blog.
In the last decade, we’ve seen learning-based systems provide transformative solutions for a wide range of perception and reasoning problems, from recognizing objects in images to recognizing and translating human speech. Recent progress in deep reinforcement learning (i.e. integrating deep neural networks into reinforcement learning systems) suggests that the same kind of success could be realized in automated decision making domains. If fruitful, this line of work could allow learning-based systems to tackle active control tasks, such as robotics and autonomous driving, alongside the passive perception tasks to which they have already been successfully applied.
Nine videos were accepted to the IJCAI video competition. We’ll update you on the winners as soon as we hear back from the conference. In the meantime – you can view the videos below or here.
The team behind the Libratus program were today announced as the latest recipients of the Marvin Minsky Medal, given by the IJCAI organisation for Outstanding Achievements in AI. Libratus made headlines in January 2017 when it beat a team of champion human poker players in a 20-day no-limit tournament.
Here’s our daily update in tweets, live from IJCAI (International Joint Conference on Artificial Intelligence) in Macau. Like yesterday, we’ll be covering tutorials and workshops.
Allen School professor Pedro Domingos has been selected as the 2019 recipient of the John McCarthy Award from the International Joint Conference on Artificial Intelligence (IJCAI). The award, which is named for one of the founders of the field of AI, recognizes established, mid-career researchers who have amassed a track record of significant research contributions that have been influential in advancing the field. Domingos is being honored by the IJCAI for his multiple contributions in machine learning and data science and for advancements in unifying logic and probability.
