43 citations · 126 across the 29 of their papers we have counts for
5 papers · 1 filter
Counting Reward Automata: Sample Efficient Reinforcement Learning Through the Exploitation of Reward Function Structure
Tristan Bester, Benjamin Rosman, Steven James +1
We present counting reward automata-a finite state machine variant capable of modelling any reward function expressible as a formal language. Unlike previous approaches, which are…
Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies
Michael Beukman, Devon Jarvis, Richard Klein +2
While reinforcement learning has achieved remarkable successes in several domains, its real-world application is limited due to many methods failing to generalise to unfamiliar con…
LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity Optimization
Muhammad U. Nasir, Sam Earle, Christopher Cleghorn +2
Large Language Models (LLMs) have emerged as powerful tools capable of accomplishing a broad spectrum of tasks. Their abilities span numerous areas, and one area where they have ma…
ROSARL: Reward-Only Safe Reinforcement Learning
Geraud Nangue Tasse, Tamlin Love, Mark Nemecek +2
An important problem in reinforcement learning is designing agents that learn to solve tasks safely in an environment. A common solution is for a human expert to define either a pe…
Hierarchically Composing Level Generators for the Creation of Complex Structures
Michael Beukman, Manuel Fokam, Marcel Kruger +5
Procedural content generation (PCG) is a growing field, with numerous applications in the video game industry and great potential to help create better games at a fraction of the c…