The central hypotheses underlying the CogPrime approach to AGI: that the cognitive synergy ensuing from integrating multiple symbolic and subsymbolic learning and memory components in an appropriate cognitive architecture and environment, can yield robust intelligence at the human level and ultimately beyond.
Phase 1: Basic Components—Completion of essential aspects of AGI system design (mathematical, conceptual and software-architecture); and implementation of initial versions of key components.
Phase 2: Artificial Toddler—On this topic, see this paper on “AGI Preschool” that was submitted from AGI-09. Refinement of design and implementation in the course of teaching the AI system to control an agent in a simulation world, according to a loosely Piagetan learning plan. Goal: an “artificial toddler” with qualitatively intelligent though not humanlike English conversation ability, involving simple sentences appropriately contextually deployed
the approximate problem-solving ability of an average four-year old human child within the context of its simulation world
Phase 3: Artificial Child—Interaction with the “artificial toddler” so as to teach it to more effectively think and communicate. Goal: an “artificial child” with the approximate problem-solving and communicational ability of an average ten-year old human child within the context of its simulation world
Phase 4: Artificial Adult—Instruction of “artificial child” in relevant topics, with a focus on bioscience, mathematics and ethics. Refinement of implementation as necessary. Goal: an intelligent, ethical “artificial adult” and young “artificial scientist”
Phase 5: Artificial Scientist—Instruction of artificial scientist in AI design and general computer science. Goal: an ethical AI capable of radically modifying and improving its own implementation in accordance with its goals
Phase 6: Artificial Intellect—An Ai created by an artificial Scientist. Goal: an ethical Intellect capable of managing the Ai scientists
In terms of the above breakdown, at present we are near the start of Phase Two, and still wrapping up some aspects of Phase One.
Can you give or direct me to more Cliff Note Summary versions of AGI research? I’d love to contribute to OpenCog as a (non-computer) scientist and I wonder if there’s anything I could help with. Am I right in guessing the code is about stuff like this?
No. I just excerpted this part because a) I thought it summarizes the key phases well and b) I’m interested in this kind of approach (I see lots of parallels between machine learning meta strategies and human learning and education.
From the book:
The OpenCogPrime roadmap from the opencog wiki:
Can you give or direct me to more Cliff Note Summary versions of AGI research? I’d love to contribute to OpenCog as a (non-computer) scientist and I wonder if there’s anything I could help with. Am I right in guessing the code is about stuff like this?
No. I just excerpted this part because a) I thought it summarizes the key phases well and b) I’m interested in this kind of approach (I see lots of parallels between machine learning meta strategies and human learning and education.