geo-infer-sim

name	geo-infer-sim
description	Agent-based simulation for geospatial environments. Use when building spatial simulations, modeling agent interactions in geographic space, running Monte Carlo spatial experiments, or comparing spatial planning scenarios.
prerequisites	{"required":["geo-infer-space","geo-infer-time"],"recommended":["geo-infer-bayes","geo-infer-act"]}
difficulty	advanced
estimated_time	60min
examples_dir	../GEO-INFER-EXAMPLES/examples/

GEO-INFER-SIM

Instructions

Core Capabilities

• Agent-based modeling: Spatial agents on grids, networks, and continuous space
• Environment simulation: Geographic environment state management, land use dynamics
• Monte Carlo: Stochastic spatial experiments with ensemble statistics
• Scenario analysis: What-if spatial scenario comparison and sensitivity analysis
• Visualization: Simulation playback, spatial animation, time-step rendering

Key Imports

from geo_infer_sim.core.simulation import SpatialSimulation
from geo_infer_sim.core.environment import GeoEnvironment
from geo_infer_sim.core.scenario import ScenarioManager
from geo_infer_sim.core.monte_carlo import MonteCarloRunner

Examples

from geo_infer_sim.core.simulation import SpatialSimulation

sim = SpatialSimulation(
    grid_size=(100, 100),
    n_agents=50,
    time_steps=200
)
sim.add_rule("diffusion", rate=0.1)
results = sim.run()
final_state = results.get_snapshot(t=200)

Guidelines

• Mesa integration in development (Alpha)

Integrations

• Integrates with AGENT for Active Inference agent behavior
• Integrates with ANT for swarm simulation
• Test: uv run python -m pytest GEO-INFER-SIM/tests/ -v