We’re pleased to announce version 0.83.5 of the Screeps GPT autonomous bot.
What’s New
New Features
- Overmind-RL Reinforcement Learning Research: Comprehensive evaluation of RL integration potential for bot AI optimization
- Created research documentation in
docs/research/overmind-rl-analysis.md - Analyzed Overmind-RL three-component architecture (Node.js backend, Python Gym wrapper, distributed training)
- Evaluated RL algorithms (PPO, DQN), neural network designs, and reward function engineering
- Assessed 7 use cases: combat micro, resource allocation, expansion, creep bodies, market trading, tasks, pathfinding
- Documented training requirements: $2k-$10k first year, 870 hours effort, GPU infrastructure
- Detailed cost-benefit analysis: RL 6x more expensive than proven Overmind patterns with uncertain ROI
- Compatibility analysis: Architecture misalignment (Python vs. TypeScript-only), 10-200ms inference latency
- Created 6-phase integration roadmap (33-48 weeks) if pursued in future
- Decision: NOT RECOMMENDED for current integration—focus on proven optimization patterns instead
- Defined revisit conditions: bot maturity (12-24 months), specific high-value use case, RL expertise, infrastructure budget
- Updated TASKS.md with research findings and alternative recommendations
- Related research: Overmind architecture (overmind-analysis.md), creep-tasks (#625), packrat (#626)
- Created research documentation in
Full Changelog: 0.83.5 on GitHub