README.md

metadata

license: cc-by-4.0
tags:
  - finance
  - defi
  - amm
  - reinforcement-learning
pretty_name: RL Execution Training Logs

RL Execution Training Logs

Per-checkpoint DQN training logs for arXiv:2607.10960 — Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator.

Primary artifacts (model checkpoints, result CSVs, code) live in the public repo github.com/egpivo/amm-lab (data/rl_equilibrium/), commit 656ae56. These training logs are supplementary reproducibility evidence — validation implementation-shortfall (IS) curves per episode, with the selected ("best") checkpoint marked — kept separately since they were briefly excluded by an overly broad .gitignore rule.

Contents

dqn_train_logs.tar.gz — 6 logs, one per DQN variant:

• dqn_train.log (dynamic duopoly, the base variant)
• dqn_train_completion_aware.log
• dqn_train_constant_duopoly.log
• dqn_train_dynamic_monopoly.log
• dqn_train_order_after.log
• dqn_train_order_random.log

Each line: ep <episode> eps <exploration rate> val IS <bps> (<elapsed s>), with <- best marking the checkpoint that was selected and shipped.

Note on reproducibility

The paper's reproducibility claim rests on the shipped .pt checkpoints being exactly re-evaluable (content-hashed in data/rl_equilibrium/m3r_run_manifest.json), not on these training curves. These logs are included for transparency, not as a correctness dependency.