Package Exports

human-logic
human-logic/dist/index.js

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Readme

Human Logic or Common Sense

Human Logic (also known as “common sense”) is based on five categories:

true = certainly positive
false = certainly negative
maybe = uncertain (could be either positive or negative)
never = impossible (neither positive nor negative)
undefined = totally unknown

This package provides the implementation of both Discrete Common Sense Logic and Fuzzy Common Sense Logic.

Discrete Common Sense Logic only allows true, false, maybe, never or undefined as a value.

In Fuzzy Common Sense Logic the value is five-dimensional unit vector. Each vector component is a fuzzy value (between 0.0 and 1.0 inclusive) of respective true, false, maybe, never or undefined category.

Migration from v1 to v2

Category type was migrated from numeric enum to string const assertions
Category type values UNDEF, FALSE, NEVER, MAYBE, TRUE are now strings (not numbers).
LogicHash interface was removed – use LogicValues interface instead.
Logic.asHash(...) was removed – use Logic.asValues(...) instead.
Logic.fromHash(...) was replaced by new method Logic.fromValues(...).

Documentation

API Documentation: https://arturania.dev/human-logic

Installation

With NPM:

npm install --save human-logic

With Yarn:

yarn add human-logic

Usage

Node v6+ syntax:

const {
  // Discrete Common Sense Logic
  Categories, UNDEF, FALSE, NEVER, MAYBE, TRUE,
  // Fuzzy Common Sense Logic
  Logic,
  // Polymorphic Functions
  not, and, or, normalize,
  // Bonus: classical fuzzy logic
  Fuzzy, FUZZY_TRUE, FUZZY_FALSE
} = require('human-logic');

ES5+ syntax:

import {
  // Discrete Common Sense Logic
  Categories, UNDEF, FALSE, NEVER, MAYBE, TRUE,
  // Fuzzy Common Sense Logic
  Logic,
  // Polymorphic Functions
  not, and, or, normalize,
  // Bonus: classical fuzzy logic
  Fuzzy, FUZZY_TRUE, FUZZY_FALSE
} from 'human-logic';

Discrete Common Sense Logic

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NOT

`undef`	`false`	`never`	`maybe`	`true`
`undef`	`true`	`maybe`	`never`	`false`

AND

	`undef`	`false`	`never`	`maybe`	`true`
`undef`	`undef`	`undef`	`undef`	`undef`	`undef`
`false`	`undef`	`false`	`false`	`false`	`false`
`never`	`undef`	`false`	`never`	`false`	`never`
`maybe`	`undef`	`false`	`false`	`maybe`	`maybe`
`true`	`undef`	`false`	`never`	`maybe`	`true`

OR

	`undef`	`false`	`never`	`maybe`	`true`
`undef`	`undef`	`undef`	`undef`	`undef`	`undef`
`false`	`undef`	`false`	`never`	`maybe`	`true`
`never`	`undef`	`never`	`never`	`true`	`true`
`maybe`	`undef`	`maybe`	`true`	`maybe`	`true`
`true`	`undef`	`true`	`true`	`true`	`true`

Usage

not(TRUE)
// => FALSE
and(MAYBE, NEVER)
// => FALSE
or(MAYBE, NEVER)
// => TRUE
Categories
// => [UNDEF, FALSE, NEVER, MAYBE, TRUE]

Fuzzy Common Sense Logic

Math Background

where "", "" and "" are classical fuzzy logic operations.

Initialization

// new instance
const value = new Logic(0.1, 0.2, 0.3, 0.1, 0.4);
// or
const value = Logic.fromValues({
  UNDEF: 0.1,
  FALSE: 0.2,
  NEVER: 0.3,
  MAYBE: 0.1,
  TRUE:  0.4 // — dominating category
});
// or
const value = Logic.fromArray([0.1, 0.2, 0.3, 0.1, 0.4]);

// Result
value.asCategory()
// => TRUE
value.get(NEVER)
// => 0.3
value.isValid() // At least one category fuzzy value is non-zero
// => true
value.eq(TRUE) // Equal to category
// => true
value.ne(MAYBE) // Not equal to category
// => true

const value = Logic.fromCategory(MAYBE);
value.asArray()
// => [0.0, 0.0, 0.0, 1.0, 0.0]
value.asValues()
// => { UNDEF: 0.0, FALSE: 0.0, NEVER: 0.0, MAYBE: 1.0, TRUE: 0.0 }
value.asValues()
// => { [UNDEF]: 0.0, [FALSE]: 0.0, [NEVER]: 0.0, [MAYBE]: 1.0, [TRUE]: 0.0 }

// Cloning
const clonedValue = value.clone();
clonedValue.asValues()
// => { [UNDEF]: 0.0, [FALSE]: 0.0, [NEVER]: 0.0, [MAYBE]: 1.0, [TRUE]: 0.0 }
clonedValue === value
// false

// Normalization
const nonNormalizedValue = Logic.fromValues({
  UNDEF: 2,
  FALSE: 3,
  NEVER: 4,
  MAYBE: 5,
  TRUE:  6
});
const normalizedValue = nonNormalizedValue.normalize();
normalizedValue.asArray()
// => [0.1, 0.15, 0.2, 0.25, 0.3]
nonNormalizedValue.getNormalized(NEVER)
// => 0.2

Logical NOT

const value = Logic.fromValues({
  UNDEF: 0.10, // 10%
  FALSE: 0.15, // 15%
  NEVER: 0.20, // 20%
  MAYBE: 0.25, // 25%
  TRUE:  0.30  // 30% — dominating category
});

// Use either class method:
value.not().asValues()
// or polymorphic function:
not(value).asValues()
// => {
//   UNDEF: 0.1,  // 10%
//   FALSE: 0.3,  // 30% — dominating category
//   NEVER: 0.25, // 25%
//   MAYBE: 0.2,  // 20%
//   TRUE:  0.15  // 15%
// }

Logical AND

const value1 = Logic.fromValues({
  UNDEF: 0.15, // 15%
  FALSE: 0.10, // 10%
  NEVER: 0.25, // 25%
  MAYBE: 0.30, // 30% — dominating category
  TRUE:  0.20  // 20%
});
const value2 = Logic.fromValues({
  UNDEF: 0.20, // 20%
  FALSE: 0.30, // 30% — dominating category
  NEVER: 0.10, // 10%
  MAYBE: 0.15, // 15%
  TRUE:  0.25  // 25%
});

// class method
value1.and(value2).asValues()
// polymorphic function
and(value1, value2).asValues()
// => {
//   UNDEF: 0.16666666666666669, // ~17%
//   FALSE: 0.25,                //  25% — dominating category
//   NEVER: 0.20833333333333334, // ~21%
//   MAYBE: 0.20833333333333334, // ~21%
//   TRUE:  0.16666666666666669  // ~17%
// }

Logical OR

// class method
value1.or(value2).asValues()
// polymorphic function
or(value1, value2).asValues()
// => {
//   UNDEF: 0.18181818181818182, // ~18%
//   FALSE: 0.09090909090909091, //  ~9%
//   NEVER: 0.22727272727272727, // ~23%
//   MAYBE: 0.2727272727272727,  // ~27% — dominating category
//   TRUE:  0.22727272727272727  // ~23%
// }

Other Operations

Accumulation of fuzzy sums with value normalization in the end:

const values: Logic[] = [
  new Logic(0.10, 0.15, 0.20, 0.25, 0.30),
  new Logic(0.30, 0.25, 0.20, 0.15, 0.10),
  new Logic(0.20, 0.25, 0.30, 0.10, 0.15),
  new Logic(0.15, 0.20, 0.25, 0.30, 0.10)
];
const sum: Logic = new Logic();
for (let index = 0; index < values.length; index += 1) {
  sum.add(values[index]);
}
sum.asValues()
// => {
//   UNDEF: 0.75,
//   FALSE: 0.85,
//   NEVER: 0.95,
//   MAYBE: 0.8,
//   TRUE:  0.65
// }
sum.normalize().asValues()
// => {
//   UNDEF: 0.1875, // 18.75%
//   FALSE: 0.2125, // 21.25%
//   NEVER: 0.2375, // 23.75%
//   MAYBE: 0.2,    // 20.00%
//   TRUE:  0.1625  // 16.25%
// }

Classical Fuzzy Logic

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Usage

FUZZY_FALSE
// => 0.0
FUZZY_TRUE
// => 1.0
not(0.67)
// => 0.33
and(0.47, 0.91)
// => 0.47
or(0.75, 0.34)
// => 0.75
normalize(1.66) === FUZZY_TRUE
// => true
normalize(-28.45) === FUZZY_FALSE
// => true
normalize(0.64)
// => 0.64

Optimized Imports

// Discrete Common Sense Logic only
import { Categories, not, and, or, UNDEF, FALSE, NEVER, MAYBE, TRUE } from 'human-logic/dist/Category';

// Fuzzy Common Sense Logic only
import { Logic, not, and, or, normalize } from 'human-logic/dist/Logic';
// When using class methods only
import { Logic } from 'human-logic/dist/Logic';

// Classical Fuzzy Logic only
import { Fuzzy, not, and, or, normalize, FUZZY_TRUE, FUZZY_FALSE } from 'human-logic/dist/Fuzzy';