Become a sponsor to Logicmμ
We are working on Human-Like AI. Symbolic AI. GOFAI.
Schank’s conceptual dependency theory has laid dormant for want of various technological advancements for so long that most scientists of the field are unaware of its successes and potential. This project is unique in that the elements it seeks to combine are novel and our usage of these elements is quite different than anything previously attempted. Narrative Intelligence has proved itself a useful process but development has halted. Unfortunately the likelihood of educational curriculums producing qualified candidates in the future is low.
We want to bring fresh life into the Artificial Intelligence field by combining several promising logical theories, and integrating a few experimental elements all our own.
Our work is based on the Conceptual Dependency Theory of Roger Schank. We arrange these into the Event Calculus of Eric Muller to form the narratives. With Michael Kifer’s F-logic we fill in the Event Calculus holes. And with the addition of John McCarthy's Elaboration Tolerance we have the ability to accept changes to the representation of facts about a subject without having to start all over. Often the addition of a few sentences describing the change suffices for humans and so should also suffice for computer programs.
There are many kinds of elaborations a person can tolerate, and they pose different problems to different logical formulations
● analogical planning (chunking): storing successful plans and adapting them to future problems
● daydreaming goals: strategies for what to think about
● hierarchical planning: achieving a goal by breaking it down into subgoals
● episode indexing in F-Logic and retrieval: mechanisms for indexing and retrieval of cases
● serendipity detection and application: a mechanism for recognizing and exploiting accidental
relationships among problems
● action mutation: a strategy for generating new possibilities when the system is stuck
Our method will create Artificial General Intelligence, and the development tools we create will be open to all.
Use of your funds :
This groundbreaking work requires a team of 8-12 highly specialized/qualified experts from multiple very specialized fields(including cognitive psychology, discursive logic ai, user-interface. etc) working full time.
Logicmoo uses your money to support this work being done in Open Source!
We are also seeking investors to fund this project (and we may create specializations for companies in the future so we can continue to pay for this work) but we are insistent that all the tools be available to developers and completely opensource.
1 sponsor has funded logicmoo’s work.
Meet the team
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aindilisInterested in AI for personal organization.
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David Whitten whittenComputer Programmer, co-founder worldvista.org, MUMPS developer, learning Delphi
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Cas-AMLearning DevOPs and Prolog. Looking to change the world.
Featured work
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logicmoo/wam_common_lisp
Allow Lisp programs to stop implementing an ad-hoc, informally-specified, bug-ridden, slow implementation of less than half of ISO-Prolog.
Common Lisp 100 -
logicmoo/prologmud
MUD Server written in Prolog using Forward chaining
Prolog 30 -
logicmoo/logicmoo_clif
Base Forward Chaining Knowledge Base Maintenance System
Prolog 18 -
logicmoo/logicmoo_ec
A SWI-Prolog Pack that lets Prolog code seamlessly switch between planners
Prolog 16 -
logicmoo/logicmoo_nlu
LogicMOO Natural Language Understanding Kit Unified into Prolog
Common Lisp 13 -
logicmoo/logicmoo_cg
Conceptual Graph (CG) Libraries in Prolog
Prolog 4