Artificial General Intelligence: 9th International Conference, AGI 2016, New York, NY, USA, July 16-19, 2016, ProceedingsBas Steunebrink, Pei Wang, Ben Goertzel Springer, 2016. jún. 24. - 364 oldal This book constitutes the refereed proceedings of the 9th International Conference on Artificial General Intelligence, AGI 2016, held in New York City, NY, USA, in July 2016 as part of HLAI 2016, the Joint Multi-Conference on Human-Level Artificial Intelligence 2016. The 24 full papers, 2 short papers, and 10 poster papers presented were carefully reviewed and selected from 67 submissions. AGI research differs from the ordinary AI research by stressing on the versatility and wholeness of intelligence, and by carrying out the engineering practice according to an outline of a system comparable to the human mind inSelf a certain sense. |
Tartalomjegyzék
| 1 | |
| 12 | |
Death and Suicide in Universal Artificial Intelligence | 23 |
Physical Complexity and Limits of Inductive Inference Systems | 33 |
OpenEnded Intelligence | 43 |
The AGI Containment Problem | 53 |
Imitation Learning as CauseEffect Reasoning | 64 |
Some Theorems on Incremental Compression | 74 |
Asymptotic Logical Uncertainty and the Benford Test | 202 |
Towards a Computational Framework for FunctionDriven Concept Invention | 212 |
System Induction Games and Cognitive Modeling as an AGI Methodology | 223 |
Integrating ModelBased Prediction and Facial Expressions in the Perception of Emotion | 234 |
A Few Notes on Multiple Theories and Conceptual Jump Size | 244 |
Generalized Temporal Induction with Temporal Concepts in a Nonaxiomatic Reasoning System | 254 |
Confidence Measures for General Value Functions | 258 |
Automatic Sampler Discovery via Probabilistic Programming and Approximate Bayesian Computation | 262 |
An Extension to Neural Networks | 84 |
RealTime GABased Probabilistic Programming in Application to Robot Control | 95 |
About Understanding | 106 |
Why Artificial Intelligence Needs a Task Theory | 118 |
Growing Recursive SelfImprovers | 129 |
Function Approximation vs SelfOrganization | 140 |
The Emotional Mechanisms in NARS | 150 |
The OpenNARS Implementation of the NonAxiomatic Reasoning System | 160 |
Integrating Symbolic and Subsymbolic Reasoning | 171 |
Integrating Axiomatic and Analogical Reasoning | 181 |
A Step Towards HumanLevel Reasoning | 192 |
How Much Computation and Distributedness is Needed in Sequence Learning Tasks? | 274 |
Analysis of Algorithms and Partial Algorithms | 284 |
Estimating Cartesian Compression via Deep Learning | 294 |
A Methodology for the Assessment of AI Consciousness | 305 |
Toward HumanLevel MassivelyParallel Neural Networks with HodgkinHuxley Neurons | 314 |
Modeling Neuromodulation as a Framework to Integrate Uncertainty in General Cognitive Architectures | 324 |
Controlling Combinatorial Explosion in Inference via Synergy with NonlinearDynamical Attention Allocation | 334 |
A Unifying MetaAlgorithm for Practical General Intelligence | 344 |
Ideas for a Reinforcement Learning Algorithm that Learns Programs | 354 |
| 363 | |
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Artificial General Intelligence: 9th International Conference, AGI 2016, New ... Bas Steunebrink,Pei Wang,Ben Goertzel Nincs elérhető előnézet - 2016 |
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