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Developmental AI Roadmap

Place to host theoretical synthesis for Developmental AI

Publications

Continual Embodied Learning

Developmental Braitenberg Vehicles

Training on Viewpoint Networks, in Observer-dependent Collective Behavior

Artificial Neural Networks vs. Biological Neural Networks

Dynammical Heterochrony

Allostasis Machines

Meta-brains Models

Gibsonian Information

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?