Life as Counterfactual Geometry: An Adversarial Theory of Biological Function

Area of Science:

• Theoretical biology
• Dynamical systems theory
• Information geometry

Background:

• Current models fail to explain biological anticipation, adaptability, and resilience.
• Biological systems operate beyond simple stimulus-response or static homeostasis.

Purpose of the Study:

• Propose a theoretical framework for understanding biological function through future trajectory geometry.
• Formalize distributions over future trajectories as a 'counterfactual manifold'.
• Analyze adaptive systems and their stability using adversarial dynamics.

Main Methods:

• Utilized information geometry and dynamical systems theory.
• Developed dual-channel adversarial dynamics to model adaptive systems.
• Analyzed system stability and identified three generic regimes: collapse, runaway sensitivity, and bounded non-convergent regulation.

Main Results:

• Adaptive systems modifying their future trajectories are generically unstable.
• Constructive adversarial dynamics can stabilize counterfactual geometry without fixed-point convergence.
• The framework predicts measurable proxies for system behavior, distinguishing between regimes.

Conclusions:

• Biological function is geometrically and dynamically understood through the stability of future possibilities.
• Disease can be interpreted as instability in this counterfactual geometry.
• This framework provides a higher-level perspective for analyzing adaptability, disease, and intervention.