Skip to main content

Research Alpha v0.4.0-alpha.1 enters review

· One min read
EXEPERT Team
Brain Research Visualizer

EXEPERT Research Alpha v0.4.0-alpha.1 is now an unreleased implementation candidate for deterministic game-environment training, local PPO experiments, and trajectory replay.

What is included​

  • One fixed-timestep, seeded Runner kernel shared by browser and Node adapters.
  • A versioned JSONL worker protocol and Gymnasium package.
  • A reproducible Stable-Baselines3 PPO example with local run artifacts.
  • A lazy-loaded Runs workspace and loopback-only job service.
  • Independent application, environment, protocol, manifest, and trajectory versions exposed through an accessible version panel.
  • MIT licensing, DCO contribution sign-offs, and explicit open-core extension seams that do not implement billing or hosted infrastructure.

Scope and privacy​

This is a prerelease candidate, not a public release or deployment. Existing Dashboard, Arcade, AI Rescue, Chat, Prompt, Observability, and Journal behavior remains available. Training data, trajectories, and model checkpoints remain in ignored local storage and are not uploaded without a separate explicit action.

The conformance target is deterministic Runner transitions for the same environment version, seed, and actions. Learned PPO weights can vary across hardware and numerical stacks.

The implementation inventory maps the delivered source areas, contracts, security boundaries, validation, and deliberately excluded hosted or commercial capabilities.