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Artificial Intelligence

LOGICMOO's goal is to enable knowledge engineering through software capable of modeling the real world in multiple levels of detail. LOGICMOO is working to provide a long overdue knowledge scaling platform for building new systems. Customizable personal assistants and better inference engines are a natural byproduct of solving these problems. This will facilitate our ultimate goal: the creation of true AGI.

Contact Us or find us on LinkedIn, Github, Slack or Twitter!


There are many ways to support LOGICMOO, we are looking for developers and investors.
LPS Timeline

LPS Timeline

on Github
45 person work years

3 year timeline,

for 10 experts

We are looking for funding to make this happen!
Fund AGI
Fund the future with trust, accessibility, intuitive design and environmental responsibility

If you're on this list we really want to talk to you!

Discursive Logic focused otologists, Schankian logicians, PDDL/Event Calc Experts Argumentative Logic Programmers, Programmers familiar with Schank's SAM/PAM/SWALE. Event Calculus Programmers (Prolog and/or LISP required C/C++ is a )

Task learning
Task learning from narrative examples

English Dialog Planning
English Dialog Planning with PDDL and Discrete Event Calculus

Cognitive Architecture

A New Cognitive Architecture





Knowledge Sharing in a Simulated Environment



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 and John Sowa's Conceptual Graphs we fill in holes declared within Event Calculus. And by using John McCarthy's Elaboration Tolerance we have the ability to model ongoing changes to the representation of facts within a given subject without having to start all over. Often the addition of a few sentences describing a 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
       storing successful plans and adapting them to future problems
                    Daydreaming Projects 
      strategies for what to think about
                    Hierarchical planning 
      achieving a goal by breaking it down into subProjects
                    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

We propose that the most important representation for the inner workings of the human mind is narrative. Our stories are very important to us and form the basis of our interaction with the world. We have designed a new cognitive architecture that allows for phenomena such as aphantasia, and for the diversity of narrative and non-narrative thought. Our unique multi-coding multi-mind theory expands on several promising little known theories of the 70's and 80's- to model an internal and external world symbolically. This allows us to create a highly adaptable model of a mental world more akin to the human mind.

For more please see The LOGICMOO WIKI.