7 papers
DSLE: A Learning Environment for Dark Souls Boss Encounters
Derin Gezgin, Jim O'Connor, Tanner Goodwin +1
We introduce the Dark Souls Learning Environment (DSLE), a containerized platform that presents all 22 boss encounters of Dark Souls: Remastered as game-playing agent benchmarks th…
PoC-Gym: Towards More Reliable LLM-Assisted Proof-of-Concept Exploit Generation
Derin Gezgin, Amartya Das, Shinhae Kim +3
Recently Large Language Models (LLMs) have been used in security-related tasks, including generating proof-of-concept (PoC) exploits. Several LLM-assisted approaches have been prop…
Playing Atari Space Invaders with Sparse Cosine Optimized Policy Evolution
Jim O'Connor, Jay B. Nash, Derin Gezgin +1
Evolutionary approaches have previously been shown to be effective learning methods for a diverse set of domains. However, the domain of game-playing poses a particular challenge f…
Evolutionary Optimization of Deep Learning Agents for Sparrow Mahjong
Jim O'Connor, Derin Gezgin, Gary B. Parker
We present Evo-Sparrow, a deep learning-based agent for AI decision-making in Sparrow Mahjong, trained by optimizing Long Short-Term Memory (LSTM) networks using Covariance Matrix…
Evolving Neural Controllers for Xpilot-AI Racing Using Neuroevolution of Augmenting Topologies
Jim O'Connor, Nicholas Lorentzen, Gary B. Parker +1
This paper investigates the development of high-performance racing controllers for a newly implemented racing mode within the Xpilot-AI platform, utilizing the Neuro Evolution of A…
SCOPE for Hexapod Gait Generation
Jim O'Connor, Jay B. Nash, Derin Gezgin +1
Evolutionary methods have previously been shown to be an effective learning method for walking gaits on hexapod robots. However, the ability of these algorithms to evolve an effect…