Planning for Real Time Event Response Management

Planning for Real Time Event Response Management

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Description

A reference volume for software professionals interested in building large intelligent agents capable of solving useful real-time problems where critical responses are called for. The focus of the book will be on the planning aspect of the problem (the requirements aspect) and discuss how different applications require different approaches for optimal solution. It will discuss where planning is important and where reaction can be an acceptable alternative. Lots of worked out examples will be included.show more

Product details

  • Hardback | 416 pages
  • 228.6 x 330.2 x 22.86mm | 1,837.04g
  • Pearson Education (US)
  • Prentice Hall
  • Upper Saddle River, United States
  • English
  • w. figs.
  • 0130951927
  • 9780130951922

Table of contents

1. Evolution of Planning. A Brief History of Planning. Types of Domains Used In AI. Conventional Planners. Pure (Hard-Wired) Reaction. Classical Real-time Planners. Book Synopsis. 2. Subsuming Planning to Reaction. Minton's Utility Function. Insect Intelligence and Robotics: The Work of Rodney Brooks. Procedural Reasoning Systems. Situated Automata and Situated Agents. Disadvantages and Next Step. 3. Integration of Planning and Reaction. The Planning to Reaction Spectrum. The Contingency Space. The Need for Deciding Between Planning and Reaction. 4. Deciding at Planning Time. Alternative Approaches. Empirical Approach. Analytical Approach. The Need for Good Real-time Components. 5. Execution Time: Reacting, (Re)Planning and Deciding. Anytime Algorithms. Action-based Decision Trees. 6. Real-time Planning. Guaranteeing Temporal Adequacy. Building Guaranteed And Unguaranteed Plans. 7. Applications. A Language Framework for Describing Reactive Behaviors. Formalizing Reaction Decisions in Critical Domains for Pedagogical Purposes. 8. Conclusion. Integration of the Ideas. Language Development. Integration with Existing Technologies. Development of Hardware. Index.show more

About David Ash

Dr. David Ash graduated from Stanford University in 1993 with his Ph.D. in artificial intelligence. After graduating, Dr. Ash worked until 1996 as a software developer, quantitative analyst, and trader at D.E. Shaw & Co., a Manhattan financial services firm. Since 1996, Dr. Ash has been employed as an artificial intelligence consultant with MindBox, Inc., providing consulting services to MindBox clients at various locations on the East Coast. Dr. Vlad Dabija holds an engineering degree in computers from the Polytechnic Institute in Bucuresti, Romania, a Ph.D. degree in artificial intelligence from Stanford University, and an MBA with Distinction from the Wharton School of the University of Pennsylvania. He worked in several computer technology, production, research, and academic institutions in the US, Japan, and Western and Eastern Europe before joining the venture capital firm CMEA Ventures.show more

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