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Artificial General Intelligence

Overview of attention for book
Cover of 'Artificial General Intelligence'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 AGI and the Knight-Darwin Law: Why Idealized AGI Reproduction Requires Collaboration
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    Chapter 2 Error-Correction for AI Safety
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    Chapter 3 Artificial Creativity Augmentation
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    Chapter 4 The Hierarchical Memory Based on Compartmental Spiking Neuron Model
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    Chapter 5 The Dynamics of Growing Symbols: A Ludics Approach to Language Design by Autonomous Agents
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    Chapter 6 Approach for Development of Engineering Tools Based on Knowledge Graphs and Context Separation
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    Chapter 7 Towards Dynamic Process Composition in the DSO Cognitive Architecture
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    Chapter 8 SAGE: Task-Environment Platform for Evaluating a Broad Range of AI Learners
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    Chapter 9 Post-turing Methodology: Breaking the Wall on the Way to Artificial General Intelligence
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    Chapter 10 Self-explaining AI as an Alternative to Interpretable AI
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    Chapter 11 AGI Needs the Humanities
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    Chapter 12 Report on “AI and Human Thought and Emotion”
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    Chapter 13 Cognitive Machinery and Behaviours
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    Chapter 14 Combinatorial Decision Dags: A Natural Computational Model for General Intelligence
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    Chapter 15 What Kind of Programming Language Best Suits Integrative AGI?
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    Chapter 16 Guiding Symbolic Natural Language Grammar Induction via Transformer-Based Sequence Probabilities
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    Chapter 17 Embedding Vector Differences Can Be Aligned with Uncertain Intensional Logic Differences
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    Chapter 18 Delta Schema Network in Model-Based Reinforcement Learning
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    Chapter 19 Information Digital Twin—Enabling Agents to Anticipate Changes in Their Tasks
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    Chapter 20 ‘OpenNARS for Applications’: Architecture and Control
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    Chapter 21 Towards AGI Agent Safety by Iteratively Improving the Utility Function
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    Chapter 22 Learning to Model Another Agent’s Beliefs: A Preliminary Approach
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    Chapter 23 An Attentional Control Mechanism for Reasoning and Learning
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    Chapter 24 Hyperdimensional Representations in Semiotic Approach to AGI
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    Chapter 25 The Conditions of Artificial General Intelligence: Logic, Autonomy, Resilience, Integrity, Morality, Emotion, Embodiment, and Embeddedness
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    Chapter 26 Position Paper: The Use of Engineering Approach in Creation of Artificial General Intelligence
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    Chapter 27 How Do You Test the Strength of AI?
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    Chapter 28 Omega: An Architecture for AI Unification
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    Chapter 29 Analyzing Elementary School Olympiad Math Tasks as a Benchmark for AGI
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    Chapter 30 The Meaning of Things as a Concept in a Strong AI Architecture
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    Chapter 31 Toward a General Believable Model of Human-Analogous Intelligent Socially Emotional Behavior
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    Chapter 32 Autonomous Cumulative Transfer Learning
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    Chapter 33 New Brain Simulator II Open-Source Software
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    Chapter 34 Experience-Specific AGI Paradigms
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    Chapter 35 Psychological Portrait of a Virtual Agent in the Teleport Game Paradigm
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    Chapter 36 Logical Probabilistic Biologically Inspired Cognitive Architecture
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    Chapter 37 An Architecture for Real-Time Reasoning and Learning
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    Chapter 38 A Model for Artificial General Intelligence
Attention for Chapter 28: Omega: An Architecture for AI Unification
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Chapter title
Omega: An Architecture for AI Unification
Chapter number 28
Book title
Artificial General Intelligence
Published by
Springer, Cham, September 2020
DOI 10.1007/978-3-030-52152-3_28
Book ISBNs
978-3-03-052151-6, 978-3-03-052152-3
Authors

Eray Özkural, Özkural, Eray

View on publisher site

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 27%
Student > Master 2 18%
Researcher 2 18%
Student > Bachelor 1 9%
Other 1 9%
Other 1 9%
Unknown 1 9%
Readers by discipline Count As %
Computer Science 8 73%
Neuroscience 1 9%
Unknown 2 18%

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