Geometric AI Agents

Agent architectures with geometric-algebra state representations

Overview

Exploratory work on agent architectures that carry state as geometric-algebra multivectors rather than flat vectors, extending the same Clifford-algebra approach used in the GW classifier and plasma control agent into general agent design.

Architecture

• Agent state represented as Clifford-algebra multivectors instead of flat vectors
• Extends the same Cl(3,0)/geometric-algebra approach used in the GW classifier and the plasma control agent into general-purpose agent design
• Likely builds on tardigrade_agent's existing geometric-algebra layers rather than starting a separate stack

Milestones

1. 01Define a first benchmark task distinct from plasma control, to test whether the approach generalizes
2. 02Compare geometric-algebra state representation against a flat-vector baseline on that benchmark
3. 03Decide whether this stays a research question or becomes a reusable library

Open questions

• Whether this is genuinely a separate project from tardigrade_agent or a generalization of it — worth settling before speccing further
• What benchmark task actually stresses the geometric representation's advantage rather than just restating plasma control