3 papers
cs.LG2026
Laplacian Representations for Decision-Time Planning
Dikshant Shehmar, Matthew Schlegel, Matthew E. Taylor +1
Planning with a learned model remains a key challenge in model-based reinforcement learning (RL). In decision-time planning, state representations are critical as they must support…
cs.LG2025
Operator Learning for Power Systems Simulation
Matthew Schlegel, Matthew E. Taylor, Mostafa Farrokhabadi
Time domain simulation, i.e., modeling the system's evolution over time, is a crucial tool for studying and enhancing power system stability and dynamic performance. However, these…
cs.HC2024
Human-like Bots for Tactical Shooters Using Compute-Efficient Sensors
Niels Justesen, Maria Kaselimi, Sam Snodgrass +12
Artificial intelligence (AI) has enabled agents to master complex video games, from first-person shooters like Counter-Strike to real-time strategy games such as StarCraft II and r…