Metadata Philosopher

How to Manage Computational Complexity

It’s easy for a logic reasoning system to cascade into a combinatorial explosion O(n!) where each time the system is evaluated more and more rules must be evaluated. So how do you get similar results in constant time O(C) or linear time O(n)? 1. Truncatio...

Output Teaches Intention!

Input Teaches Expectation; Output Teaches Intent AEIOU: aeio unit : affert expectation intention output unit a *e *I o Future a and o train *e and *i, respectively a and e are continuous *i and o are ballistic A and e can modulate *i and o Output tr...

Reasoning from Explicit Statements

Here we reimagine the Socrates "Simple Logic Problem" from earlier in a way where we just describe general lexical rules for learning. We write down a few rules and just tell the program "Socrates is a man. All men are mortal. Also, Socrates is dead." Then...

Sequence and Declaration

Newly implemented sequence reasoning example. Runs as test/conflict_is.test. # declarations: the:Art korean:Adj conflict:N was:V a:Art war:N # standard grammar priors: |VP <= [|Adv] |V [{|NP,|S} ] |NP <= [|Art] [|Adj] |N [|PP] |PP <= |Prep |NP |S <= |N...

Simple Logic Problem

Here I will demonstrate a simple logic problem using the set network compiler. socrates // Let's say there's a socrates socrates:man // Socrates is a man |man=>|mortal // A man is mortal ?socrates|man // is Socrates a man? YES ?socrates|mortal // is...

Types of Implication in Set Networks

There are three types of implications available in set networks: Association, Expectation, and Attribution. Type Implication Implicator Test Example of Test Implication A => B A&B A&B => C Expectation A => *B A B A B => C Attribution A:B A|B...

Metaphor

What is the fundamental structure of information? What is the common structure that can equally describe the rigors of math and logic, but also describe the subtleties and nuance of art and poetry and language itself? What structure can handle all informat...

Math and English grammar examples

|math: <a> ‘=‘ = ‘=‘ <a> <a> x = x <a> <a> ‘-‘ = ‘-‘ ‘+’ <a> <a> ‘+’ = ‘+’ <a> <a> ‘/‘ = ‘(‘ 1 ‘/‘ ‘)’ x <a> |english: | S <= NP [Aux] VP | NP <= [Art] N [PP] | VP <= V [{NP,S}] | PP <= Prep NP | NP <= [Po...

Machine learning methods in symbolic form

Machine Learning methods in symbolic form: Bay: @s1 -> @s2 Gen: <{@s_k_1,...,@s_k_n}> So incrementally try @s_k for outcome @s2 Hypothesis testing Imagination Creativity Ana: {@s1,{v1,@s2}} -> {@s1,{v2,@s3}} This like this Con: {@s1,@s2} -> @s3 Categori...

Set structure in language

Set structure in language: 1 - @s array can contain s, @v, or @s 2 - @v array has one v and may contain s, @s 3 - v is a v-class symbol (a relational symbol) 4 - s is a non v-class symbol (all other symbols) 5 - the root idea of a statement is @s 6 - a @v...