Research Radar · Experimental implementation
Agent Forge
Minimal Python reasoning loops for agent–environment interaction.
What it investigates
AgentForge isolates the basic observe, think, and act loop used in agent–environment interaction.
Implementation record
The repository pairs a ReasoningAgent with a small grid-world environment. The agent stores observations, selects an action, and applies it to the environment; the environment owns state, movement rules, items, and step counts. The intentionally small surface makes the control loop inspectable.
Public record
The linked research item is the public source recorded for this Research Radar build. It provides context for the implementation; this page does not claim to reproduce its results. The repository and its documentation are the current public materials for inspecting the build itself.
Scope and limitations
The grid world is a pedagogical reference environment. It does not establish that the same rules generalize to open-ended environments, learned policies, or deployed autonomous systems.