Caretaker Theory introduction - Intelligence And Artificial Consciousness

1. Introduction To Caretaker Theory
By Dilshad Mustafa
Copyright © Dilshad Mustafa 2018. All Rights Reserved.
https://github.com/dilshadmustafa/RoyAI
Intelligence
And
Artificial Consciousness

2. Objectives:
1) Create and develop Caretaker Theory to provide a theory and model for implementing
Artificial Intelligence and Artificial Consciousness.
2) To research and identify principles of Brain function.
2) Develop a Computational Intelligence and Thinking system with Artificial Consciousness
similar to Human thinking.
3) Create and invent Caretaker Semantic Language (CSL) to express Human Memorizing,
Learning and Thinking system giving rise to Artificial Consciousness.
4) Develop Caretaker Software Architecture (CSA), a Software Approach with highly scalable
Cluster Computing system that can be applied at very large scale and uses existing BigData
systems like HDFS, Scality, Akka, Alluxio, HBase, Java, Clojure, etc.
Copyright © Dilshad Mustafa 2018. All Rights Reserved.

3. Copyright © Dilshad Mustafa 2018. All Rights Reserved.
Caretaker:
1) There are set of Caretakers.
2) Each Caretaker takes care of one specific area of concern.
3) There might be a few hundred Caretakers. Lets assume 100 Caretakers.
Specific Algorithms:
1) There is no “Master Algorithm”. The issue with “one Master Algorithm to handle all” is its
very difficult to formulate such algorithm.
2) Instead of one Master Algorithm there are millions of Specific Algorithms.
3) Each Specific Algorithm does only one specific set of steps.
4) There are Hierarchical Layers of Specific Algorithms.
5) Specific Algorithms in each layer handle algorithm steps for granularity associated with that
layer.
6) Each Specific Algorithm Agent implements one Specific Algorithm at one layer.

4. List of Specific Algorithms:
1) Try-Record
2) What-To-Try
3) Peek-Classify
4) Ask-WhatWhyWhereWhenHow
5) Answer-Search
6) Do-Action
7) Plan-Ahead
8) Plan-Now
9) React-Hunger
10)React-Pain
11)React-Joy
12)Survive-Danger
13)Address-Failure
14)Address-Success
15)Memory-Store
16)Memory-Recall
17)Memory-Predict
New Specific Algorithms will be added on a need basis.
Copyright © Dilshad Mustafa 2018. All Rights Reserved.

5. L2L1 L3 Semantic
Language
Proto
Language
Language
Outline
Detection,
etc.
Edge
Detection,
etc.
Object
Detection,
etc.
Semantic
Association,
etc.
Proto
Language
Communication
Language-
based
Communication
Memory Storage, Recall & Pattern Recognition
using Neural Network
Specific Algorithms using Neural Network
Eyes
Image
Copyright © Dilshad Mustafa 2018. All Rights Reserved.

6. Caretaker Data Structures
Data Structures:
1) Column Structures
2) Row Structures
3) Semantic Pointer e.g. (image thumbnail, SHA2 256-bit address, timestamp)
4) Associative Memory Recall, Content Addressable e.g. (image thumbnail, SHA2
256-bit Address)
5) Similarity Grade Measure e.g. how close a pattern is matching
Column Structure:
1) Column Structure of one or more Trees of Column Structures and Row Structures.
2) Nodes in Trees can be a Column Structure or Row Structure or Neural Network
Unit.
3) A Tree can have one or more Nodes.
Copyright © Dilshad Mustafa 2018. All Rights Reserved.

7. Caretaker Data Structures (cont’d)
Row Structure:
1) Row Structure of one or more Trees of Column Structures and Row Structures.
2) Row Structure can connect across Column Structures.
Copyright © Dilshad Mustafa 2018. All Rights Reserved.