001465260 000__ 03657nam\\22005893i\4500 001465260 001__ 1465260 001465260 003__ MiAaPQ 001465260 005__ 20230702003437.0 001465260 006__ m\\\\\o\\d\\\\\\\\ 001465260 007__ cr\cn\nnnunnun 001465260 008__ 230628s2022\\\\xx\\\\\\o\\\\\|||\0\eng\d 001465260 020__ $$a9781643682457 001465260 020__ $$z9781643682440 001465260 035__ $$a(MiAaPQ)EBC29070505 001465260 035__ $$a(Au-PeEL)EBL29070505 001465260 035__ $$a(OCoLC)1311322262 001465260 040__ $$aMiAaPQ$$beng$$erda$$epn$$cMiAaPQ$$dMiAaPQ 001465260 050_4 $$aQ335 .N48 2022 001465260 0820_ $$a006.3 001465260 1001_ $$aHitzler, P. 001465260 24510 $$aNeuro-Symbolic Artificial Intelligence :$$bthe State of the Art. 001465260 250__ $$a1st ed. 001465260 264_1 $$aAmsterdam :$$bIOS Press, Incorporated,$$c2022. 001465260 264_4 $$c©2022. 001465260 300__ $$a1 online resource (410 pages). 001465260 336__ $$atext$$btxt$$2rdacontent 001465260 337__ $$acomputer$$bc$$2rdamedia 001465260 338__ $$aonline resource$$bcr$$2rdacarrier 001465260 4901_ $$aFrontiers in Artificial Intelligence and Applications Ser. ;$$vv.342 001465260 5050_ $$aIntro -- Title Page -- Preface: The 3rd AI wave is coming, and it needs a theory -- Introduction -- Contents -- Chapter 1. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation -- Chapter 2. Symbolic Reasoning in Latent Space: Classical Planning as an Example -- Chapter 3. Logic Meets Learning: From Aristotle to Neural Networks -- Chapter 4. Graph Reasoning Networks and Applications -- Chapter 5. Answering Natural-Language Questions with Neuro-Symbolic Knowledge Bases -- Chapter 6. Tractable Boolean and Arithmetic Circuits -- Chapter 7. Neuro-Symbolic AI = Neural + Logical + Probabilistic AI -- Chapter 8. A Constraint-Based Approach to Learning and Reasoning -- Chapter 9. Spike-Based Symbolic Computations on Bit Strings and Numbers -- Chapter 10. Explainable Neuro-Symbolic Hierarchical Reinforcement Learning -- Chapter 11. Neuro-Symbolic Semantic Reasoning -- Chapter 12. Learning Reasoning Strategies in End-to-End Differentiable Proving -- Chapter 13. Generalizable Neuro-Symbolic Systems for Commonsense Question Answering -- Chapter 14. Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning -- Chapter 15. Human-Centered Concept Explanations for Neural Networks -- Chapter 16. Abductive Learning -- Chapter 17. Logic Tensor Networks: Theory and Applications -- Author Index. 001465260 506__ $$aAccess limited to authorized users. 001465260 588__ $$aDescription based on publisher supplied metadata and other sources. 001465260 650_0 $$aArtificial intelligence. 001465260 650_0 $$aComputational intelligence. 001465260 650_0 $$aNeural computers. 001465260 655_0 $$aElectronic books 001465260 7001_ $$aSarker, M. K. 001465260 77608 $$iPrint version:$$aHitzler, P.$$tNeuro-Symbolic Artificial Intelligence: the State of the Art$$dAmsterdam : IOS Press, Incorporated,c2022$$z9781643682440 001465260 830_0 $$aFrontiers in Artificial Intelligence and Applications Ser. 001465260 852__ $$bebk 001465260 85640 $$3ProQuest Ebook Central Academic Complete $$uhttps://univsouthin.idm.oclc.org/login?url=https://ebookcentral.proquest.com/lib/usiricelib-ebooks/detail.action?docID=29070505$$zOnline Access 001465260 909CO $$ooai:library.usi.edu:1465260$$pGLOBAL_SET 001465260 980__ $$aBIB 001465260 980__ $$aEBOOK 001465260 982__ $$aEbook 001465260 983__ $$aOnline