Overview
- Field: Machine Learning / Reinforcement Learning Benchmarks
- Authors: Derin Gezgin, Jim O'Connor, Tanner Goodwin
- Released: 2026-08-11
- arXiv: 2508.03798
- New benchmark: DSLE exposes 22 real-time, high-dimensional, sparsely-rewarded boss fights as a Gymnasium-compatible RL benchmark running against the live game.
- Recommended starter suite: DSLE-5 covers five distinct combat archetypes for controlled comparison.
- Baselines tested: random policy, expert system, evolutionary baseline, PPO, and DQN from pixels.
- Only the tutorial boss is solvable: expert and evolutionary methods reach 63% and 43% peak win rates on *Asylum Demon*; all other four DSLE-5 bosses remain unbeaten.
- Deep RL does not learn: PPO and DQN achieve at most 0.33% win rate on the tutorial boss and 0% elsewhere, despite tens of hours of wall-clock training.
- Full sweep is largely unsolved: the evolutionary baseline wins only a few early-game bosses out of all 22 encounters, even with favorable stats.
- Evaluation beyond win rate: failure is characterized by survival time and damage dealt; some agents survive nearly a minute while dealing almost no damage.
- arXiv: https://arxiv.org/abs/2508.03798
Summary
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 through a Gymnasium-style interface. DSLE combines real-time combat, high-dimensional visual input, and sparse terminal rewards, with each environment step being a real action executed against the running game.
To support controlled comparison, we define DSLE-5, a representative five-boss subset spanning:
1. A melee fight 2. A spatially constrained arena 3. An environmental-hazard fight 4. A multi-target fight 5. A fast final-boss fight
We recommend DSLE-5 as the starting suite for agents built on DSLE.
On DSLE-5 we evaluate a random policy, an expert system, an evolutionary baseline, and PPO and DQN agents trained from visual input. The expert system and evolutionary baseline each defeat the tutorial boss *Asylum Demon* (peak win rates of 63% and 43%, respectively), but none of the five methods defeat the other four bosses in DSLE-5. PPO and DQN show no measurable learning within budgets that already require tens of hours of wall-clock time per run (at most 0.33% win rate on the tutorial boss and 0% elsewhere).
A broader study runs the evolutionary baseline across all 22 encounters; with an advantageous full level-50 stat build it wins only a handful of additional early-game bosses, with the rest unwon. Failure cases range from deaths in under ten seconds in narrow, multi-target encounters to near-minute-long stalemates with negligible damage dealt. We report these results through survival time and damage dealt rather than win rate alone.