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Parallel Processing for Artificial Intelligence 2.

By: Kumar, V.
Contributor(s): Kitano, H | Suttner, C. B.
Material type: TextTextSeries: eBooks on Demand.Machine Intelligence and Pattern Recognition: Publisher: Amsterdam : Elsevier Science, 2015Description: 1 online resource (248 p.).ISBN: 9781483295756.Subject(s): Artificial intelligence | Parallel processing (Electronic computers)Genre/Form: Electronic books.Additional physical formats: Print version:: Parallel Processing for Artificial Intelligence 2DDC classification: 006.3 Online resources: Click here to view this ebook.
Contents:
Front Cover -- Parallel Processingfor Artificial Intelligence 2 -- Copyright Page -- Table of Contents -- PREFACE -- SECTION 1: ARCHITECTURES -- Chapter 1. Hybrid Systems on a Multi-Grain Parallel Architecture -- Abstract -- 1. Introduction -- 2. Hybrid systems -- 3. ArMenX -- 4. Implementation of multiple granularity algorithms on Ar-MenX -- 5. Conclusion -- References -- Chapter 2. An Abstract Machine for Implementing Connectionist and Hybrid Systems on Multi-processor Architectures -- Abstract -- 1. Introduction -- 2. Hybrid systems for new AI applications
3. The Cellular Abstract Machine (CAM) -- 4. Implementation of a hybrid model on the CAM: an example -- 5. Multi-processor implementation of the CAM -- 6. Advancement of the implementation and conclusion -- Acknowledgements -- References -- Chapter 3. A Dense, Massively Parallel Architecture -- 1. INTRODUCTION -- 2. DESCRIPTION OF THE GRAPH CLASS -- 3. DIAMETER AND MEAN DISTANCE -- 4. ROUTING -- 5. CONCLUSION AND FUTURE WORK -- REFERENCES -- SECTION 2: LANGUAGES -- Chapter 4. Using Confluence to Control Parallel Production Systems -- 1. Introduction
2. A Brief Introduction to Term Rewriting Systems -- 3. Relating Production Systems to Term Rewriting Systems -- 4. Determining Confluence Among Production Rule Sets -- 5. Examples -- 6. Summary and Future Work -- References -- Chapter 5. Toward An Architecture Independent High Level Parallel Programming Model For Artificial Intelligence -- Abstract -- 1. Introduction -- 2. Design Considerations -- 3. The Programming Model -- 4. Examples -- 5. Exploiting Parallelism -- 6. Development Status -- 7. Conclusions -- References
Chapter 6. An Object-Oriented Approach for Programming the Connection Machine -- Abstract -- 1. Programming Model -- 2. A more detailed view -- 3. Conclusion -- References -- Chapter 7. Automatic Parallelisation of LISP programs -- Abstract -- 1. Introduction -- 2. Parallel Analysis -- 3. The PARALLEL Subsystem -- 4. Discussion -- 5. References -- SECTION 3: GENERAL ALGORITHMS -- Chapter 8.Simulation Analysis of Static Partitioning with Slackness -- Abstract -- 1. Introduction -- 2. Simulation Analysis -- 3. Related Work -- 4. Summary -- References
Chapter 9. A distributed realization for constraint satisfaction -- 1. INTRODUCTION -- 2. THE CSP -- 3. RELATED WORK -- 4. OUR DISTRIBUTED APPROACH -- 5. A MULTI-MASTER ENVIRONMENT -- 6. FINAL REMARKS -- REFERENCES -- Chapter 10. A First Step Towards the Massively Parallel Game-Tree Search : a SIMD Approach -- Abstract -- 1. Introduction -- 2. Minimax theory -- 3· α-β pruning -- 4. Search parallelization techniques -- 5. Motivations -- 6· SIMD α-β algorithm -- 7. Implementation on CM-2 -- 8. Empirical results -- 9. Concluding remarks and future works -- References
Chapter 11. Initialization of Parallel Branch-and-bound Algorithms
Summary: With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (AI) is gaining greater importance in the computer science environment. Many applications have been implemented and delivered but the field is still considered to be in its infancy. This book assembles diverse aspects of research in the area, providing an overview of the current state of technology. It also aims to promote further growth across the discipline. Contributions have been grouped according to their
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Item type Current location Call number URL Status Date due Barcode
Electronic Book UT Tyler Online
Online
QA76.58 .P37775 2014 (Browse shelf) http://uttyler.eblib.com/patron/FullRecord.aspx?p=1877051 Available EBL1877051

Front Cover -- Parallel Processingfor Artificial Intelligence 2 -- Copyright Page -- Table of Contents -- PREFACE -- SECTION 1: ARCHITECTURES -- Chapter 1. Hybrid Systems on a Multi-Grain Parallel Architecture -- Abstract -- 1. Introduction -- 2. Hybrid systems -- 3. ArMenX -- 4. Implementation of multiple granularity algorithms on Ar-MenX -- 5. Conclusion -- References -- Chapter 2. An Abstract Machine for Implementing Connectionist and Hybrid Systems on Multi-processor Architectures -- Abstract -- 1. Introduction -- 2. Hybrid systems for new AI applications

3. The Cellular Abstract Machine (CAM) -- 4. Implementation of a hybrid model on the CAM: an example -- 5. Multi-processor implementation of the CAM -- 6. Advancement of the implementation and conclusion -- Acknowledgements -- References -- Chapter 3. A Dense, Massively Parallel Architecture -- 1. INTRODUCTION -- 2. DESCRIPTION OF THE GRAPH CLASS -- 3. DIAMETER AND MEAN DISTANCE -- 4. ROUTING -- 5. CONCLUSION AND FUTURE WORK -- REFERENCES -- SECTION 2: LANGUAGES -- Chapter 4. Using Confluence to Control Parallel Production Systems -- 1. Introduction

2. A Brief Introduction to Term Rewriting Systems -- 3. Relating Production Systems to Term Rewriting Systems -- 4. Determining Confluence Among Production Rule Sets -- 5. Examples -- 6. Summary and Future Work -- References -- Chapter 5. Toward An Architecture Independent High Level Parallel Programming Model For Artificial Intelligence -- Abstract -- 1. Introduction -- 2. Design Considerations -- 3. The Programming Model -- 4. Examples -- 5. Exploiting Parallelism -- 6. Development Status -- 7. Conclusions -- References

Chapter 6. An Object-Oriented Approach for Programming the Connection Machine -- Abstract -- 1. Programming Model -- 2. A more detailed view -- 3. Conclusion -- References -- Chapter 7. Automatic Parallelisation of LISP programs -- Abstract -- 1. Introduction -- 2. Parallel Analysis -- 3. The PARALLEL Subsystem -- 4. Discussion -- 5. References -- SECTION 3: GENERAL ALGORITHMS -- Chapter 8.Simulation Analysis of Static Partitioning with Slackness -- Abstract -- 1. Introduction -- 2. Simulation Analysis -- 3. Related Work -- 4. Summary -- References

Chapter 9. A distributed realization for constraint satisfaction -- 1. INTRODUCTION -- 2. THE CSP -- 3. RELATED WORK -- 4. OUR DISTRIBUTED APPROACH -- 5. A MULTI-MASTER ENVIRONMENT -- 6. FINAL REMARKS -- REFERENCES -- Chapter 10. A First Step Towards the Massively Parallel Game-Tree Search : a SIMD Approach -- Abstract -- 1. Introduction -- 2. Minimax theory -- 3· α-β pruning -- 4. Search parallelization techniques -- 5. Motivations -- 6· SIMD α-β algorithm -- 7. Implementation on CM-2 -- 8. Empirical results -- 9. Concluding remarks and future works -- References

Chapter 11. Initialization of Parallel Branch-and-bound Algorithms

With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (AI) is gaining greater importance in the computer science environment. Many applications have been implemented and delivered but the field is still considered to be in its infancy. This book assembles diverse aspects of research in the area, providing an overview of the current state of technology. It also aims to promote further growth across the discipline. Contributions have been grouped according to their

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