Swarm Production Runtime (SPR) Core v0.1.0-alpha

This is the first architectural release of the Swarm Production Runtime (SPR) — a decentralized multi-agent system inspired by ant colony pheromone dynamics.

⚙️ Core Features
🐜 Decentralized Agent System
Worker agents operate without central control
Scout agents explore new task space
Reproduction logic enables dynamic scaling
🧬 Pheromone-Based Memory
Distributed reinforcement learning via Redis
Successful task paths increase pheromone strength
Automatic decay prevents system stagnation
🔁 Self-Scaling Runtime
Load-based worker spawning logic
No fixed capacity limits
Horizontal scaling ready (Docker/Kubernetes compatible)
📡 Task Ingestion API
Simple HTTP interface for task submission
Event-driven queue system (Redis-backed)

🏗️ Architecture Status
This release includes:
Core swarm execution loop
Worker agent runtime
Scout exploration logic
Pheromone reinforcement engine
Basic auto-scaling mechanism
Docker deployment structure

⚠️ Known Limitations
No advanced failure recovery orchestration yet
No persistent long-term global optimization model
No visualization layer (pheromone map UI not included yet)
Reproduction logic is heuristic-based (not ML-driven yet)

🔮 Roadmap (Next Versions)
v0.2.0 → Reinforcement learning pheromone optimization
v0.3.0 → Distributed graph intelligence layer
v0.4.0 → Swarm visualization dashboard
v1.0.0 → Production-grade orchestration engine

🧪 Philosophy
SPR is built on a single principle:
Intelligence emerges from local rules, not central control.