In this milestone we will develop the broad definitions of the AGI framework. Basing our architecture on the Frankel-Bedworth model for information fusion we will define the modular components of a forward-backward / processing-motivation AGI system operating at multiple levels of abstraction.

Project white paper

$10,000 USD

White paper adequately describes the background to our work, the essence of the control and estimation architecture from 2000, and how we have used it as a springboard to develop a novel AGI framework.

In this milestone we will extend the model to cover the two key aspects of AGI: self-directed learning and socio-ethical conformity. Learning should be modularised in such a way that supports continuous improvement while maintaining the ability to generalise. Conformity to expectations from external influences will form a key element of the top-down control signal. In this milestone we will also introduce the multiple levels of abstraction with which the AGI system can operate.

Specification document

$5,000 USD

Specification document describes the leaning and conformity elements of our novel AGI framework, together with the levels of abstraction which enable top-down motivation in addition to self-directed goal setting. We will also list a number of use-cases, and how we see them fitting into our framework. We will include ChatBots, Humanoid Robots and Virtual Agents among our use cases.

For this milestone we will develop an implementation of a very basic AI system which illustrates the behavior of designs based on our framework. Detailed specifications will be finalised nearer the time but we will construct a system which encompasses sensing perception decision making and learning of the forward loop; plus expectation preference and motivation of the backward loop. We suggest a very simple 2D environment consisting of colored polygonal shapes which interact in a specified way and under the constraints of a prescribed rule system. The system will interact autonomously with its environment using reinforcement learning; and with a “teacher” using supervised learning. The idea here is not to illuminate the boundaries of what the architecture can encompass but to provide a “Hello world” illustration of how it might fit into the Hyperon AGI Framework. Key elements of even a simple demonstrator are motivation and prioritization both of which we intend to illustrate in some basic form.

Framework demo implemented in MeTTa

$10,000 USD

Demonstrator software is functional, written in MeTTa, and adequately showcases our novel AGI framework using inferencing paradigms as necessary e.g. PLNs or NNs.

This milestone comprises the production of a final version of the research paper describing the Florisson-Frankel-Bedworth AGI architecture. It will outline our findings and detail the behavior of a software implementation of the demonstrator system. The paper will be based on the white paper reports of milestones 1 and 2. It will include relevant sections on background motivation insights and experiments. We will conclude with an honest description of any limitations and remaining challenges our thoughts on how the framework might be further developed or extended and an indicative roadmap of how these might be addressed in future work.

Research paper detailing the Florisson-Frankel-Bedworth AGI architecture

$5,000 USD

A research paper of sufficient quality is submitted, or in sufficient condition to be submitted, to a relevant AGI journal or conference. A presentation of our findings to the SingularityNET community also organised and available if requested.