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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
  2. Altmetric Badge
    Chapter 1 Self-Modification of Policy and Utility Function in Rational Agents
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    Chapter 2 Avoiding Wireheading with Value Reinforcement Learning
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    Chapter 3 Death and Suicide in Universal Artificial Intelligence
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    Chapter 4 Ultimate Intelligence Part II: Physical Complexity and Limits of Inductive Inference Systems
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    Chapter 5 Open-Ended Intelligence
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    Chapter 6 The AGI Containment Problem
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    Chapter 7 Imitation Learning as Cause-Effect Reasoning
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    Chapter 8 Some Theorems on Incremental Compression
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    Chapter 9 Rethinking Sigma’s Graphical Architecture: An Extension to Neural Networks
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    Chapter 10 Real-Time GA-Based Probabilistic Programming in Application to Robot Control
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    Chapter 11 About Understanding
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    Chapter 12 Why Artificial Intelligence Needs a Task Theory
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    Chapter 13 Growing Recursive Self-Improvers
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    Chapter 14 Different Conceptions of Learning: Function Approximation vs. Self-Organization
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    Chapter 15 The Emotional Mechanisms in NARS
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    Chapter 16 The OpenNARS Implementation of the Non-Axiomatic Reasoning System
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    Chapter 17 Integrating Symbolic and Sub-symbolic Reasoning
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    Chapter 18 Integrating Axiomatic and Analogical Reasoning
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    Chapter 19 Embracing Inference as Action: A Step Towards Human-Level Reasoning
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    Chapter 20 Asymptotic Logical Uncertainty and the Benford Test
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    Chapter 21 Towards a Computational Framework for Function-Driven Concept Invention
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    Chapter 22 System Induction Games and Cognitive Modeling as an AGI Methodology
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    Chapter 23 Integrating Model-Based Prediction and Facial Expressions in the Perception of Emotion
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    Chapter 24 A Few Notes on Multiple Theories and Conceptual Jump Size
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    Chapter 25 Generalized Temporal Induction with Temporal Concepts in a Non-axiomatic Reasoning System
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    Chapter 26 Introspective Agents: Confidence Measures for General Value Functions
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    Chapter 27 Automatic Sampler Discovery via Probabilistic Programming and Approximate Bayesian Computation
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    Chapter 28 How Much Computation and Distributedness is Needed in Sequence Learning Tasks?
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    Chapter 29 Analysis of Algorithms and Partial Algorithms
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    Chapter 30 Estimating Cartesian Compression via Deep Learning
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    Chapter 31 A Methodology for the Assessment of AI Consciousness
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    Chapter 32 Toward Human-Level Massively-Parallel Neural Networks with Hodgkin-Huxley Neurons
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    Chapter 33 Modeling Neuromodulation as a Framework to Integrate Uncertainty in General Cognitive Architectures
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    Chapter 34 Controlling Combinatorial Explosion in Inference via Synergy with Nonlinear-Dynamical Attention Allocation
  36. Altmetric Badge
    Chapter 35 Probabilistic Growth and Mining of Combinations: A Unifying Meta-Algorithm for Practical General Intelligence
  37. Altmetric Badge
    Chapter 36 Ideas for a Reinforcement Learning Algorithm that Learns Programs
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

twitter
16 X users
facebook
3 Facebook pages
wikipedia
2 Wikipedia pages
reddit
1 Redditor

Readers on

mendeley
5 Mendeley
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Title
Artificial General Intelligence
Published by
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-319-41649-6
ISBNs
978-3-31-941648-9, 978-3-31-941649-6
Authors

James Babcock, Janos Kramar, Roman Yampolskiy

Editors

Bas Steunebrink, Pei Wang, Ben Goertzel

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 20%
Professor > Associate Professor 1 20%
Unknown 3 60%
Readers by discipline Count As %
Computer Science 1 20%
Engineering 1 20%
Unknown 3 60%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 April 2023.
All research outputs
#2,974,411
of 25,508,813 outputs
Outputs from Lecture notes in computer science
#570
of 8,165 outputs
Outputs of similar age
#47,690
of 400,427 outputs
Outputs of similar age from Lecture notes in computer science
#106
of 582 outputs
Altmetric has tracked 25,508,813 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,165 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 400,427 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 582 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.