The goal-driven self-programming system, called AERA (Autocatalytic Endogenous Reflective Architecture),[2] started out with only a small set of seed knowledge (a few pages of "given" code) and autonomously expanded its capabilities through self-reconfiguration, writing the equivalent of thousands of lines of code on its own, to enable it to perform such a realtime TV interview.
The constructivist artificial intelligence methodology[6] proposed by Thórisson to addresses the numerous significant challenges involved in building artificial general intelligence AGI systems, by replacing the top-down architectural design approaches that are ubiquitous today with methods that allow a system to autonomously manage its own cognitive growth.
This involves a shift of focus from manual design of mental functions to the principles from which intelligent systems can grow through self-organization.
The methodology was inspired in part by Piaget's stance towards cognitive development and motivated by the level of operational complexity that will be required for realizing AGI systems in contrast to what can be achieved with even large teams of human software engineers and software designers relying on methods of manual construction.
Fusing some of the best principles from prior AI methods, including subsumption architecture, modular construction, and behavior-oriented design (BOD), and classical AI, CDM presents iterative design steps that lead to the creation of a network of named interacting modules, communicating via explicitly-typed streams and discrete messages.
[11] In August 2024 Thórisson and his co-authors received the "AGI Society Award" for their paper "Argument-Driven Planning & Autonomous Explanation Generation"[12] at the Intl.