In this meetup, we will have talks and workshops on everything related to Reinforcement Learning. We will be discussing the latest research in this domain and its applications on real world problems. We will also get expert advice on the applications of open source reinforcement learning tools from Facebook, OpenAI and DeepMind. We will invite speakers from the academia and industry to share their projects with the reinforcement learning community in London.
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Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning
Featuring Sanjeevan Ahilan
How can reinforcement learning agents learn to cooperate and solve problems? In this talk, I will introduce the field of multi-agent reinforcement learning and various approaches that have been taken to address this challenge. I will then introduce our own framework, called Feudal Multi-Agent...data reinforcement-learning autonomous-agents ai
Knowledge Transfer in Reinforcement Learning
Featuring Jin Cong Ho
How can reinforcement learning algorithms benefit from knowledge learned from previous tasks? In this talk, we will dive into recent works in transfer learning, multi-task learning and meta-learning. We will look at several transfer approaches and compare their differences. After the talk, you...discovery artificial-intelligence transfer-learning reinforcement-learning
Human-Level Control Through Deep Reinforcement Learning
Featuring Skif Pankov
In this talk Skif will discuss his implementation of Deepmind's paper on Reinforcement Learning for Atari Games published by Nature. It is considered a landmark paper in Reinforcement Learning literature in which an RL agent received human level performance a number of Atari games.devops ai deep-learning reinforcement-learning
Monte Carlo Tree Search in Reinforcement Learning
Featuring Ali Chaudhry
Monte Carlo Tree Search has proven to be one of the most productive techniques in Reinforcement Learning. It has produced state of the results in problems with humongous state spaces like Chess and Go. Ali will present the theory behind this Monte Carlo Tress Search and share its use cases.data reinforcement-learning
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