The GOD Engine SDK gives you access to seven universal force models, temporal prediction, and agent-based simulation — in a few lines of code.
Each force is an independent, composable module. Use one or wire all seven together for full simulation.
Directed intelligence computation. Models agent intent, conviction strength, and insight efficiency under chaos.
Adaptive memory decay. Controls belief purging, state forgetting, and the return-to-zero force that makes room for new signal.
Logistic feedback loops. Self-reinforcing growth below capacity, self-limiting above. Models compounding and collapse.
Friction modeling. Fixed costs, speed costs, and quadratic scale-impact costs. Nothing is free at any scale.
Ethical gradient field. Computes the cost slope around harmful states. Not a wall — a continuous cost surface.
Exploration drive. Counter-cyclical search with a guaranteed non-zero floor. Walks wider when signal is weakest.
Multi-agent coupling matrix. Adversarial at low coupling, cooperative at high coupling. The interaction force between all agents.
The unified Agent class. Runs all seven forces in a single tick loop. Drop in any domain parameters — it handles the rest.
Create an agent, define its domain parameters, and let the engine compute the seven forces on every tick. The same code works for markets, biology, social systems, or anything else that evolves under uncertainty.
from godengine import Agent, Environment # Create an agent with domain parameters agent = Agent("market_alpha", domain="finance") # Build the environment env = Environment() env.register(agent) # Run the prediction cycle for t in range(1000): state = agent.tick(env, dt=0.01) # Read the foresight prediction = agent.foresight(horizon=48) print(prediction.direction) # → 'bullish' print(prediction.confidence) # → 0.847 print(prediction.forces) # → {7 force breakdown}
From first install to multi-agent simulation at scale.
Install, configure, and run your first agent in under 5 minutes. Zero dependencies beyond NumPy.
Read guide →Deep dive into each force module — parameters, configuration, domain tuning, and edge cases.
Explore forces →Coupling matrices, noise channels, cooperative/adversarial dynamics, and emergent behavior at scale.
Build agents →Pre-configured parameter sets for finance, social dynamics, biology, geopolitics, and more.
Browse domains →How the engine builds probability maps over all possible states and collapses them to action.
Learn theory →Complete API documentation. Every class, method, and parameter. Auto-generated from source.
View API →Finance. Biology. Social simulation. Climate modeling. Consciousness research. Same seven forces. Same three terms. Your domain.