2 citations · 2 across the 2 of their papers we have counts for
4 papers
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…
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…
Loss Bounds and Time Complexity for Speed Priors
Daniel Filan, Marcus Hutter, Jan Leike
This paper establishes for the first time the predictive performance of speed priors and their computational complexity. A speed prior is essentially a probability distribution tha…
Sequential Extensions of Causal and Evidential Decision Theory
Tom Everitt, Jan Leike, Marcus Hutter
Moving beyond the dualistic view in AI where agent and environment are separated incurs new challenges for decision making, as calculation of expected utility is no longer straight…