Reinforcement Learning on a rust simulation that only gives delayed rewards.
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Updated
Apr 29, 2026 - Python
Reinforcement Learning on a rust simulation that only gives delayed rewards.
Staged, reproducible RL hyperparameter search for Isaac Lab + skrl: declare a task in one YAML, run screen → refine → verify with fair canonical evals, live early-stop of dead runs, shared-GPU guards and termination-cause reports. A winner only counts after it reproduces.
Gridworld problem with dynamic obstacles implemented in PyGame GUI and solved using traditional RL agent (Q-learning) and deep RL agent (PPO algorithm).
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