Developmental AI

Place to host theoretical synthesis for Developmental AI.

Preprint

Embodied Continual Learning Across Developmental Time Via Developmental Braitenberg Vehicles link

Switch modes vs. Convergence and constraint.

  • Path Dependence vs. Innateness (mixed features).

  • canalization function.

Analogies and Mathematical Parallels

  • epigenetic landscapes vs. gradient descent (quantitative trajectories, energy minimization).

  • population-based approach (agents with diversity rather than pure minimization).

  • are developmental trajectories always maximally efficient? Phenotypic buffering, pleiotropy, minimally viable phenotypes (not developmentally lethal).

Potential tasks:

  • theory development (@ansonzlim), fleshing out and defining different components and their relations.

  • computational verification / principle "testing" (inspiration from free energy principle)

  • real-world impacts: Gary Marcus "Robust AI" ; Lisa Feldmen Barret, clinical approaches

Next steps?

  1. Differentiate Developmental AI from "Regular AI", and what we mean by "development" (sequential acquisition vs. emergent morphogenesis)?
  • what is DevAI (guiding document)?

  • examination of the various conceptual components and start fitting them together - a Wiki?

Roadmap

  • DevAI, Gibsonian Information, Allostasis Machines.