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Artificial General Intelligence

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

Table of Contents

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    Book Overview
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    Chapter 1 Self-Modification and Mortality in Artificial Agents
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    Chapter 2 Delusion, Survival, and Intelligent Agents
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    Chapter 3 Coherence Progress: A Measure of Interestingness Based on Fixed Compressors
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    Chapter 4 Sequential Constant Size Compressors for Reinforcement Learning
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    Chapter 5 Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments
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    Chapter 6 Optimal Direct Policy Search
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    Chapter 7 Nonlinear-Dynamical Attention Allocation via Information Geometry
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    Chapter 8 An Information Theoretic Representation of Agent Dynamics as Set Intersections
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    Chapter 9 On More Realistic Environment Distributions for Defining, Evaluating and Developing Intelligence
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    Chapter 10 Structural Emergence in Partially Ordered Sets Is the Key to Intelligence
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    Chapter 11 Integrating Perception and Cognition for AGI
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    Chapter 12 Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network
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    Chapter 13 Comparing Humans and AI Agents
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    Chapter 14 The LIDA Framework as a General Tool for AGI
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    Chapter 15 From Memory to Problem Solving: Mechanism Reuse in a Graphical Cognitive Architecture
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    Chapter 16 Rational Universal Benevolence: Simpler, Safer, and Wiser Than “Friendly AI”
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    Chapter 17 The Collection of Physical Knowledge and Its Application in Intelligent Systems
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    Chapter 18 Rationality and General Intelligence
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    Chapter 19 Wagging the Dog: Human vs. Machine Inference of Causality in Visual Sequences
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    Chapter 20 Learning Problem Solving Skills from Demonstration: An Architectural Approach
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    Chapter 21 Compression and Intelligence: Social Environments and Communication
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    Chapter 22 OpenPsi: Realizing Dörner’s “Psi” Cognitive Model in the OpenCog Integrative AGI Architecture
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    Chapter 23 Extending Cognitive Architectures with Semantic Resources
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    Chapter 24 A Motivational System for Cognitive AI
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    Chapter 25 On Fast Deep Nets for AGI Vision
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    Chapter 26 Considerations for a Neuroscience-Inspired Approach to the Design of Artificial Intelligent Systems
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    Chapter 27 Brain Anatomy and Artificial Intelligence
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    Chapter 28 Information, Utility and Bounded Rationality
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    Chapter 29 A Family of Gödel Machine Implementations
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    Chapter 30 Reinforcement Learning and the Bayesian Control Rule
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    Chapter 31 Societies of Intelligent Agents
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    Chapter 32 Towards a General Vision System Based on Symbol-Relation Grammars and Bayesian Networks
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    Chapter 33 Reasoning in Non-Axiomatic Logic: A Case Study in Medical Diagnosis
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    Chapter 34 Measuring Agent Intelligence via Hierarchies of Environments
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    Chapter 35 Learning What to Value
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    Chapter 36 Learning the States: A Brain Inspired Neural Model
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    Chapter 37 AGI Architecture Measures Human Parameters and Optimizes Human Performance
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    Chapter 38 Multigame Playing by Means of UCT Enhanced with Automatically Generated Evaluation Functions
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    Chapter 39 From Sensorimotor Graphs to Rules: An Agent Learns from a Stream of Experience
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    Chapter 40 Three Hypotheses about the Geometry of Mind
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    Chapter 41 Imprecise Probability as a Linking Mechanism between Deep Learning, Symbolic Cognition and Local Feature Detection in Vision Processing
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    Chapter 42 Generalization of Figure-Ground Segmentation from Binocular to Monocular Vision in an Embodied Biological Brain Model
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    Chapter 43 The Illusion of Internal Joy
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    Chapter 44 Philosophically Inspired Concept Acquisition for Artificial General Intelligence
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    Chapter 45 Machine Lifelong Learning: Challenges and Benefits for Artificial General Intelligence
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    Chapter 46 A Demonstration of Combining Spatial and Temporal Perception
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    Chapter 47 Towards Heuristic Algorithmic Memory
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    Chapter 48 Complex Value Systems in Friendly AI
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    Chapter 49 Real-World Limits to Algorithmic Intelligence
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    Chapter 50 AGI and Neuroscience: Open Sourcing the Brain
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    Chapter 51 What Makes a Brain Smart? Reservoir Computing as an Approach for General Intelligence
Attention for Chapter 33: Reasoning in Non-Axiomatic Logic: A Case Study in Medical Diagnosis
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Citations

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Summary Dimensions citations
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Chapter title
Reasoning in Non-Axiomatic Logic: A Case Study in Medical Diagnosis
Chapter number 33
Book title
Artificial General Intelligence
Published in
Lecture notes in computer science, January 2011
DOI 10.1007/978-3-642-22887-2_33
Book ISBNs
978-3-64-222886-5, 978-3-64-222887-2
Authors

Pei Wang, Seemal Awan

Editors

Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 36%
Student > Master 3 21%
Researcher 3 21%
Professor 1 7%
Other 1 7%
Other 1 7%
Readers by discipline Count As %
Computer Science 8 57%
Social Sciences 2 14%
Agricultural and Biological Sciences 1 7%
Neuroscience 1 7%
Unknown 2 14%

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