geo-infer-agent

This framework enables autonomous agents for geospatial decision-making by supporting Active Inference, BDI, and Reinforcement Learning architectures, allowing agents to perceive, reason, and act within complex spatial environments.

Yes, you can coordinate a multi-agent system for spatial mapping in Python, facilitating multi-agent communication, coordination, and lifecycle management to collaboratively map unknown terrain and ensure complete coverage.

Available agent architectures for autonomous systems in complex spatial environments include Active Inference, BDI, Reinforcement Learning, and Rule-Based agents, providing diverse decision-making capabilities for spatial reasoning.

Yes, deploying autonomous agents requires integration with core GEO-INFER modules, which supply the underlying spatial reasoning and active inference components needed for geospatial applications.

The best way to manage the lifecycle of individual agents in geospatial applications is using this framework's lifecycle management features to create, deploy, monitor, and manage individual agents or multi-agent systems.

You create and run a data collector agent by using the geo-infer-agent skill with the provided configuration, enabling quick deployment of agents for spatial data collection and environmental perception.