AscensionAI

Project Documentation

Start here for the architecture, experiments, technical writeup, demo assets, portfolio framing, and public dashboard behind AscensionAI.

Core Docs

Architecture

Distributed trainer/worker topology, checkpoint sync, stale rollout rejection, failure handling, scaling points, and hands-off self-healing cloud operation.

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Headless Simulator & Search-Combat

The June pivot to the sts_lightspeed C++ simulator, the variant series that proved combat execution was the universal wall, and the search-combat + diagnosed-macro stack that produced the first winning agents (mainline_v3).

Read the latest (011)

Headless Cloud Deployment

Running the worker/trainer stack headless on a GPU-less GCP spot VM: one-shot installer, Xvfb + software GL, Java 8, spot preemption recovery, and the nine bring-up challenges with fixes.

Read deployment notes

Technical Writeup

Implementation detail on observations, actions, reward shaping, behavior cloning, PPO, parallel training, and limitations.

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Experiment Reports

The full arc, from BC baseline and live-game PPO through the simulator variant series to the first winning agents (009–011), backed by the public experiment registry.

Open experiments

Scripts Reference

Plain-English guide to each training, evaluation, environment, plotting, and logging script.

Read script guide

Dashboard

Static results viewer with embedded public metrics and support for loading local CSV files.

Open dashboard

Portfolio and Resume Framing

Recruiter-facing summary, public demo assets, and resume-ready bullets.

Open portfolio page