16 citations · 18 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
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…
Augmentative Topology Agents For Open-Ended Learning
Muhammad Umair Nasir, Michael Beukman, Steven James +1
In this work, we tackle the problem of open-ended learning by introducing a method that simultaneously evolves agents and increasingly challenging environments. Unlike previous ope…
Towards Objective Metrics for Procedurally Generated Video Game Levels
Michael Beukman, Steven James, Christopher Cleghorn
With increasing interest in procedural content generation by academia and game developers alike, it is vital that different approaches can be compared fairly. However, evaluating p…