Artificial general intelligence : 13th International Conference, AGI 2020, St. Petersburg, Russia, September 16-19, 2020, Proceedings /: 13th International Conference, AGI 2020, St. Petersburg, Russia, September 16-19, 2020, Proceedings. (2020)
- Record Type:
- Book
- Title:
- Artificial general intelligence : 13th International Conference, AGI 2020, St. Petersburg, Russia, September 16-19, 2020, Proceedings /: 13th International Conference, AGI 2020, St. Petersburg, Russia, September 16-19, 2020, Proceedings. (2020)
- Main Title:
- Artificial general intelligence : 13th International Conference, AGI 2020, St. Petersburg, Russia, September 16-19, 2020, Proceedings
- Other Titles:
- AGI 2020
- Further Information:
- Note: Ben Goertzel, Aleksandr I. Panov, Alexey Potapov, Roman Yampolskiy (eds.).
- Other Names:
- Goertzel, Ben
Panov, Aleksandr I
Potapov, Alexey
Yampolskiy, Roman V, 1979-
AGI (Conference), 13th - Contents:
- Intro -- Preface -- Organization -- Contents -- AGI and the Knight-Darwin Law: Why Idealized AGI Reproduction Requires Collaboration -- 1 Introduction -- 2 The Intuitive Ordinal Notation System -- 3 Intuitive Ordinal Intelligence -- 4 The Knight-Darwin Law -- 4.1 Motivation for Multi-agent Approaches to AGI -- 4.2 Motivation for AGI Variety -- 4.3 AGI Genetics -- 5 Discussion -- 5.1 What Does Definition6 Really Have to Do with Intelligence? -- 5.2 Can't an AGI Just Print a Copy of Itself? -- 5.3 Prohibitively Expensive Simulation -- 6 Conclusion -- References -- Error-Correction for AI Safety 1 Motivation -- 2 Transdisciplinary System Clustering -- 3 Type I and Type II AI Safety -- 3.1 Type I AI Risks -- 3.2 Type II AI Nature and Type II AI Risks -- 4 Summary and Outlook -- References -- Artificial Creativity Augmentation -- 1 Deconstructing Anthropic Creativity -- 1.1 Creative Outcome in Context -- 1.2 Creative Process -- 2 Constructing ACA -- 2.1 Methods for Anthropic Creativity Augmentation -- 2.2 Addressing the Augmentation of Artificial Creativity -- 3 Conclusion -- References -- The Hierarchical Memory Based on Compartmental Spiking Neuron Model -- 1 Introduction 2 The Problem Analysis -- 3 The Memory Architecture -- 3.1 The Structure -- 3.2 The Model Inputs/Outputs -- 4 The Experiment -- 5 Conclusion -- References -- The Dynamics of Growing Symbols: A Ludics Approach to Language Design by Autonomous Agents -- 1 Introduction -- 2 Linking Symbols with Dynamics -- 3Intro -- Preface -- Organization -- Contents -- AGI and the Knight-Darwin Law: Why Idealized AGI Reproduction Requires Collaboration -- 1 Introduction -- 2 The Intuitive Ordinal Notation System -- 3 Intuitive Ordinal Intelligence -- 4 The Knight-Darwin Law -- 4.1 Motivation for Multi-agent Approaches to AGI -- 4.2 Motivation for AGI Variety -- 4.3 AGI Genetics -- 5 Discussion -- 5.1 What Does Definition6 Really Have to Do with Intelligence? -- 5.2 Can't an AGI Just Print a Copy of Itself? -- 5.3 Prohibitively Expensive Simulation -- 6 Conclusion -- References -- Error-Correction for AI Safety 1 Motivation -- 2 Transdisciplinary System Clustering -- 3 Type I and Type II AI Safety -- 3.1 Type I AI Risks -- 3.2 Type II AI Nature and Type II AI Risks -- 4 Summary and Outlook -- References -- Artificial Creativity Augmentation -- 1 Deconstructing Anthropic Creativity -- 1.1 Creative Outcome in Context -- 1.2 Creative Process -- 2 Constructing ACA -- 2.1 Methods for Anthropic Creativity Augmentation -- 2.2 Addressing the Augmentation of Artificial Creativity -- 3 Conclusion -- References -- The Hierarchical Memory Based on Compartmental Spiking Neuron Model -- 1 Introduction 2 The Problem Analysis -- 3 The Memory Architecture -- 3.1 The Structure -- 3.2 The Model Inputs/Outputs -- 4 The Experiment -- 5 Conclusion -- References -- The Dynamics of Growing Symbols: A Ludics Approach to Language Design by Autonomous Agents -- 1 Introduction -- 2 Linking Symbols with Dynamics -- 3 Ludics: The Logic of Rules -- 3.1 Convergent Perspectives via Orthogonality of Designs -- 3.2 Behaviors as Interactive Semantics -- 4 Conclusion -- References -- Approach for Development of Engineering Tools Based on Knowledge Graphs and Context Separation -- 1 Introduction 2 Proposed Approach -- 2.1 Context Meaning -- 2.2 Class-Object Interchangeability -- 3 Examples from Systems Engineering -- 3.1 Example of Realization a Structure Application -- 3.2 Components Schema App -- 4 Discussion -- 5 Conclusion -- References -- Towards Dynamic Process Composition in the DSO Cognitive Architecture -- 1 Introduction -- 2 Dynamic Process Composition -- 3 Anomaly Detection: An Example -- 4 Discussion -- 5 Conclusion -- References -- SAGE: Task-Environment Platform for Evaluating a Broad Range of AI Learners -- 1 Introduction -- 2 Related Work 3 SAGE: Overview of Structure and Use -- 3.1 Requirements -- 3.2 Architecture: Model-View-Controller-Agents (MVC-A) -- 4 Proof of Concept -- 5 Conclusions and Future Work -- References -- Post-turing Methodology: Breaking the Wall on the Way to Artificial General Intelligence -- 1 Introduction. Turing Methodology for Assessment of Artificial Intelligence (1950-2014) -- 2 Methodology for the Critical Analysis of the Turing Test -- 3 The Continuum of Turing-Like Tests and Its Limitations -- 3.1 From Verbal to Non-verbal -- 3.2 From Virtual to Physical -- 3.3 Four Areas for AGI Development … (more)
- Publisher Details:
- Cham : Springer
- Publication Date:
- 2020
- Extent:
- 1 online resource
- Subjects:
- 006.3
Artificial intelligence -- Congresses
Electronic books
Electronic books - Languages:
- English
- ISBNs:
- 9783030521523
3030521524 - Related ISBNs:
- 3030521516
9783030521516 - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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- British Library HMNTS - ELD.DS.515397
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- 03_099.xml