LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity Optimization

1 code implementation • 1 Jun 2023 • Muhammad U. Nasir, Sam Earle, Christopher Cleghorn, Steven James, Julian Togelius

By merging the code-generating abilities of LLMs with the diversity and robustness of QD solutions, we introduce \texttt{LLMatic}, a Neural Architecture Search (NAS) algorithm.

Code Generation Image Classification +1

Training Feedforward Neural Networks with Bayesian Hyper-Heuristics

1 code implementation • 29 Mar 2023 • Arné Schreuder, Anna Bosman, Andries Engelbrecht, Christopher Cleghorn

The process of training feedforward neural networks (FFNNs) can benefit from an automated process where the best heuristic to train the network is sought out automatically by means of a high-level probabilistic-based heuristic.

Towards Objective Metrics for Procedurally Generated Video Game Levels

1 code implementation • 25 Jan 2022 • 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.