Description: Agents in the Long Game of AI by Marjorie Mcshane, Sergei Nirenburg "An argument if favor of hybrid AI systems over purely ML ones to increase machine transparency and human trust"-- FORMAT Paperback CONDITION Brand New Publisher Description A novel approach to hybrid AI aimed at developing trustworthy agent collaborators.A novel approach to hybrid AI aimed at developing trustworthy agent collaborators.The vast majority of current AI relies wholly on machine learning (ML). However, the past thirty years of effort in this paradigm have shown that, despite the many things that ML can achieve, it is not an all-purpose solution to building human-like intelligent systems. One hope for overcoming this limitation is hybrid AI- that is, AI that combines ML with knowledge-based processing. In Agents in the Long Game of AI, Marjorie McShane, Sergei Nirenburg, and Jesse English present recent advances in hybrid AI with special emphases on content-centric computational cognitive modeling, explainability, and development methodologies.At present, hybridization typically involves sprinkling knowledge into an ML black box. The authors, by contrast, argue that hybridization will be best achieved in the opposite way- by building agents within a cognitive architecture and then integrating judiciously selected ML results. This approach leverages the power of ML without sacrificing the kind of explainability that will foster societys trust in AI. This book shows how we can develop trustworthy agent collaborators of a type not being addressed by the "ML alone" or "ML sprinkled by knowledge" paradigms-and why it is imperative to do so. Author Biography Marjorie McShane and Sergei Nirenburg are Professors in the Cognitive Science Department and Co-Directors of the Language-Endowed Intelligent Agents Lab at Rensselaer Polytechnic Institute.Jesse English is Senior Research Scientist in the Language-Endowed Intelligent Agents Lab at Rensselaer Polytechnic Institute. Table of Contents ContentsChapter 1. Setting the StageChapter 2. Content-Centric Cognitive ModelingChapter 3. Knowledge BasesChapter 4. Language Understanding and GenerationChapter 5. The Trajectory of Microtheory Development: The Example of CoreferenceChapter 6. Dialog as Perception, Reasoning and ActionChapter 7. LearningChapter 8. ExplanationChapter 9. Knowledge AcquisitionChapter 10. Disrupting the Dominant ParadigmNotesReferencesIndex Details ISBN0262549425 Author Sergei Nirenburg Publisher MIT Press Ltd Year 2024 ISBN-13 9780262549424 Format Paperback Imprint MIT Press Subtitle Computational Cognitive Modeling for Trustworthy, Hybrid AI Country of Publication United States Audience General DEWEY 006.3 Pages 350 Illustrations 18 BLACK AND WHITE ILLUS. ISBN-10 0262549425 Publication Date 2024-09-03 US Release Date 2024-09-03 UK Release Date 2024-09-03 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:161350173;
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