Search Results for author: Humphrey Munn

Found 2 papers, 1 papers with code

Modularity in NEAT Reinforcement Learning Networks

1 code implementation • 13 May 2022 • Humphrey Munn, Marcus Gallagher

Modularity is essential to many well-performing structured systems, as it is a useful means of managing complexity [8].

reinforcement-learning Reinforcement Learning (RL)

Paper
Code

Assessing Evolutionary Terrain Generation Methods for Curriculum Reinforcement Learning

no code implementations • 29 Mar 2022 • David Howard, Josh Kannemeyer, Davide Dolcetti, Humphrey Munn, Nicole Robinson

To allow direct comparison between both direct and indirect representations, we assess the impact of a range of representation-agnostic MAP-Elites feature descriptors that compute metrics directly from the generated terrain meshes.

reinforcement-learning Reinforcement Learning (RL)

Paper
Add Code

Cannot find the paper you are looking for? You can Submit a new open access paper.