243 citations · 597 across the 9 of their papers we have counts for
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cs.AI2017
Universal Reinforcement Learning Algorithms: Survey and Experiments
John Aslanides, Jan Leike, Marcus Hutter
Many state-of-the-art reinforcement learning (RL) algorithms typically assume that the environment is an ergodic Markov Decision Process (MDP). In contrast, the field of universal…
cs.AI2017★ 6 cited
AIXIjs: A Software Demo for General Reinforcement Learning
John Aslanides
Reinforcement learning is a general and powerful framework with which to study and implement artificial intelligence. Recent advances in deep learning have enabled RL algorithms to…
cs.AI2017
Generalised Discount Functions applied to a Monte-Carlo AImu Implementation
Sean Lamont, John Aslanides, Jan Leike +1
In recent years, work has been done to develop the theory of General Reinforcement Learning (GRL). However, there are few examples demonstrating these results in a concrete way. In…