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Artificial General Intelligence: 8th International Conference, AGI 2015, AGI 2015, Berlin, Germany, July 22-25, 2015, Proceedings
Two Attempts to Formalize Counterpossible Reasoning in Deterministic Settings
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Author(s):
Nate Soares
,
Benja Fallenstein
Publication date
(Online):
July 15 2015
Publisher:
Springer International Publishing
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Some Principles of the Theory of Testing Hypotheses
E. Lehmann
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Newcomb’s Problem and Two Principles of Choice
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Publication date (Print):
2015
Publication date (Online):
July 15 2015
Pages
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DOI:
10.1007/978-3-319-21365-1_17
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b781b2e1-72aa-48bd-b390-cde829605b24
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Book chapters
pp. 3
Modeling Motivation in MicroPsi 2
pp. 14
Genetic Programming on Program Traces as an Inference Engine for Probabilistic Languages
pp. 25
Scene Based Reasoning
pp. 35
Anchoring Knowledge in Interaction: Towards a Harmonic Subsymbolic/Symbolic Framework and Architecture of Computational Cognition
pp. 46
Safe Baby AGI
pp. 50
Observation, Communication and Intelligence in Agent-Based Systems
pp. 60
Reflective Variants of Solomonoff Induction and AIXI
pp. 70
Are There Deep Reasons Underlying the Pathologies of Today’s Deep Learning Algorithms?
pp. 80
Speculative Scientific Inference via Synergetic Combination of Probabilistic Logic and Evolutionary Pattern Recognition
pp. 90
Stochastic Tasks: Difficulty and Levin Search
pp. 101
Instrumental Properties of Social Testbeds
pp. 111
Towards Human-Level Inductive Functional Programming
pp. 121
Anytime Bounded Rationality
pp. 131
Ultimate Intelligence Part I: Physical Completeness and Objectivity of Induction
pp. 142
Towards Emotion in Sigma: From Appraisal to Attention
pp. 152
Inferring Human Values for Safe AGI Design
pp. 156
Two Attempts to Formalize Counterpossible Reasoning in Deterministic Settings
pp. 166
Bounded Cognitive Resources and Arbitrary Domains
pp. 177
Using Localization and Factorization to Reduce the Complexity of Reinforcement Learning
pp. 187
Towards Flexible Task Environments for Comprehensive Evaluation of Artificial Intelligent Systems and Automatic Learners
pp. 197
Assumptions of Decision-Making Models in AGI
pp. 208
Issues in Temporal and Causal Inference
pp. 218
The Space of Possible Mind Designs
pp. 231
A Definition of Happiness for Reinforcement Learning Agents
pp. 241
Expression Graphs
pp. 251
Toward Tractable Universal Induction Through Recursive Program Learning
pp. 261
How Can Cognitive Modeling Benefit from Ontologies? Evidence from the HCI Domain
pp. 272
C-Tests Revisited: Back and Forth with Complexity
pp. 283
A New View on Grid Cells Beyond the Cognitive Map Hypothesis
pp. 293
Programming Languages and Artificial General Intelligence
pp. 301
From Specialized Syntax to General Logic: The Case of Comparatives
pp. 310
Decision-Making During Language Understanding by Intelligent Agents
pp. 320
Plan Recovery in Reactive HTNs Using Symbolic Planning
pp. 331
Optimization Framework with Minimum Description Length Principle for Probabilistic Programming
pp. 341
Can Machines Learn Logics?
pp. 352
Comparing Computer Models Solving Number Series Problems
pp. 362
Emotional Concept Development
pp. 373
The Cyber-Physical System Approach Towards Artificial General Intelligence: The Problem of Verification
pp. 394
On the Limits of Recursively Self-Improving AGI
pp. 404
Gödel Agents in a Scalable Synchronous Agent Framework
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