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Artificial General Intelligence
Learning What to Value
other
Author(s):
Daniel Dewey
Publication date
(Print):
2011
Publisher:
Springer Berlin Heidelberg
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Speculations Concerning the First Ultraintelligent Machine
Irving John Good
(1966)
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Universal Algorithmic Intelligence: A Mathematical Top→Down Approach
Marcus Hutter
(2007)
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Book Chapter
Publication date (Print):
2011
Pages
: 309-314
DOI:
10.1007/978-3-642-22887-2_35
SO-VID:
ebcd2a0d-ea85-4065-9aa0-802e3b81ae25
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Book chapters
pp. 1
Self-Modification and Mortality in Artificial Agents
pp. 11
Delusion, Survival, and Intelligent Agents
pp. 21
Coherence Progress: A Measure of Interestingness Based on Fixed Compressors
pp. 31
Sequential Constant Size Compressors for Reinforcement Learning
pp. 41
Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments
pp. 52
Optimal Direct Policy Search
pp. 62
Nonlinear-Dynamical Attention Allocation via Information Geometry
pp. 72
An Information Theoretic Representation of Agent Dynamics as Set Intersections
pp. 82
On More Realistic Environment Distributions for Defining, Evaluating and Developing Intelligence
pp. 92
Structural Emergence in Partially Ordered Sets Is the Key to Intelligence
pp. 102
Integrating Perception and Cognition for AGI
pp. 112
Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network
pp. 122
Comparing Humans and AI Agents
pp. 133
The LIDA Framework as a General Tool for AGI
pp. 143
From Memory to Problem Solving: Mechanism Reuse in a Graphical Cognitive Architecture
pp. 153
Rational Universal Benevolence: Simpler, Safer, and Wiser Than “Friendly AI”
pp. 163
The Collection of Physical Knowledge and Its Application in Intelligent Systems
pp. 174
Rationality and General Intelligence
pp. 184
Wagging the Dog: Human vs. Machine Inference of Causality in Visual Sequences
pp. 194
Learning Problem Solving Skills from Demonstration: An Architectural Approach
pp. 204
Compression and Intelligence: Social Environments and Communication
pp. 212
OpenPsi: Realizing Dörner’s “Psi” Cognitive Model in the OpenCog Integrative AGI Architecture
pp. 222
Extending Cognitive Architectures with Semantic Resources
pp. 232
A Motivational System for Cognitive AI
pp. 243
On Fast Deep Nets for AGI Vision
pp. 247
Considerations for a Neuroscience-Inspired Approach to the Design of Artificial Intelligent Systems
pp. 255
Brain Anatomy and Artificial Intelligence
pp. 269
Information, Utility and Bounded Rationality
pp. 275
A Family of Gödel Machine Implementations
pp. 281
Reinforcement Learning and the Bayesian Control Rule
pp. 286
Societies of Intelligent Agents
pp. 291
Towards a General Vision System Based on Symbol-Relation Grammars and Bayesian Networks
pp. 297
Reasoning in Non-Axiomatic Logic: A Case Study in Medical Diagnosis
pp. 303
Measuring Agent Intelligence via Hierarchies of Environments
pp. 309
Learning What to Value
pp. 315
Learning the States: A Brain Inspired Neural Model
pp. 321
AGI Architecture Measures Human Parameters and Optimizes Human Performance
pp. 327
Multigame Playing by Means of UCT Enhanced with Automatically Generated Evaluation Functions
pp. 333
From Sensorimotor Graphs to Rules: An Agent Learns from a Stream of Experience
pp. 340
Three Hypotheses about the Geometry of Mind
pp. 346
Imprecise Probability as a Linking Mechanism between Deep Learning, Symbolic Cognition and Local Feature Detection in Vision Processing
pp. 351
Generalization of Figure-Ground Segmentation from Binocular to Monocular Vision in an Embodied Biological Brain Model
pp. 357
The Illusion of Internal Joy
pp. 363
Philosophically Inspired Concept Acquisition for Artificial General Intelligence
pp. 370
Machine Lifelong Learning: Challenges and Benefits for Artificial General Intelligence
pp. 376
A Demonstration of Combining Spatial and Temporal Perception
pp. 382
Towards Heuristic Algorithmic Memory
pp. 388
Complex Value Systems in Friendly AI
pp. 394
Real-World Limits to Algorithmic Intelligence
pp. 401
AGI and Neuroscience: Open Sourcing the Brain
pp. 407
What Makes a Brain Smart? Reservoir Computing as an Approach for General Intelligence
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