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