398 citations · 1.8k across the 163 of their papers we have counts for
4 papers · 1 filter
A Game-Theoretic Analysis of the Off-Switch Game
Tobias Wängberg, Mikael Böörs, Elliot Catt +2
The off-switch game is a game theoretic model of a highly intelligent robot interacting with a human. In the original paper by Hadfield-Menell et al. (2016), the analysis is not fu…
Count-Based Exploration in Feature Space for Reinforcement Learning
Jarryd Martin, Suraj Narayanan Sasikumar, Tom Everitt +1
We introduce a new count-based optimistic exploration algorithm for Reinforcement Learning (RL) that is feasible in environments with high-dimensional state-action spaces. The succ…
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…