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000756197 019__ $$a952571203
000756197 020__ $$a9783319321134$$q(electronic book)
000756197 020__ $$a3319321137$$q(electronic book)
000756197 020__ $$z9783319321110
000756197 035__ $$aSP(OCoLC)ocn952934114
000756197 035__ $$aSP(OCoLC)952934114$$z(OCoLC)952571203
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000756197 050_4 $$aQ335
000756197 050_4 $$aRC321-580
000756197 08204 $$a006.3$$223
000756197 08204 $$a610
000756197 1001_ $$aHo, Seng-Beng.
000756197 24510 $$aPrinciples of noology$$h[electronic resource] :$$btoward a theory and science of intelligence /$$cSeng-Beng Ho/
000756197 260__ $$aSwitzerland :$$bSpringer,$$c2016.
000756197 300__ $$a1 online resource (444 pages)
000756197 336__ $$atext$$btxt$$2rdacontent
000756197 337__ $$acomputer$$bc$$2rdamedia
000756197 338__ $$aonline resource$$bcr$$2rdacarrier
000756197 4901_ $$aSocio-Affective Computing ;$$vv.3
000756197 504__ $$aIncludes bibliographical references and index.
000756197 5050_ $$aRapid Unsupervised Effective Causal Learning -- A General Noological Framework -- Conceptual Grounding and Operational Representation -- Causal Rules, Problem Solving, and Operational Representation -- The Causal Role of Sensory Information -- Application to the StarCraft Game Environment -- A Grand Challenge for Noology and Computational Intelligence -- Affect Driven Noological Processes -- Summary and Beyond -- Appendix A: Causal vs Reinforcement Learning -- Appendix B: Rapid Effective Causal Learning Algorithm.
000756197 506__ $$aAccess limited to authorized users.
000756197 520__ $$aThe idea of this book is to establish a new scientific discipline, "noology," under which a set of fundamental principles are proposed for the characterization of both naturally occurring and artificial intelligent systems. The methodology adopted in Principles of Noology for the characterization of intelligent systems, or "noological systems," is a computational one, much like that of AI. Many AI devices such as predicate logic representations, search mechanisms, heuristics, and computational learning mechanisms are employed but they are recast in a totally new framework for the characterization of noological systems. The computational approach in this book provides a quantitative and high resolution understanding of noological processes, and at the same time the principles and methodologies formulated are directly implementable in AI systems. In contrast to traditional AI that ignores motivational and affective processes, under the paradigm of noology, motivational and affective processes are central to the functioning of noological systems and their roles in noological processes are elucidated in detailed computational terms. In addition, a number of novel representational and learning mechanisms are proposed, and ample examples and computer simulations are provided to show their applications. These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving. Semantic grounding allows an AI/noological system to "truly understand" the meaning of the knowledge it encodes. This issue is extensively explored. This is a highly informative book providing novel and deep insights into intelligent systems which is particularly relevant to both researchers and students of AI and the cognitive sciences.
000756197 588__ $$aDescription based on print version record.
000756197 650_0 $$aArtificial intelligence.
000756197 650_0 $$aComputational neuroscience.
000756197 650_0 $$aMedicine.
000756197 650_0 $$aScience.
000756197 650_0 $$aNeurosciences.
000756197 650_0 $$aComputational intelligence.
000756197 77608 $$iPrint version:$$aHo, Seng-Beng$$tPrinciples of Noology : Toward a Theory and Science of Intelligence$$dCham : Springer International Publishing,c2016$$z9783319321110
000756197 830_0 $$aSocio-Affective Computing ;$$vv. 3
000756197 852__ $$bebk
000756197 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-32113-4$$zOnline Access$$91397441.1
000756197 909CO $$ooai:library.usi.edu:756197$$pGLOBAL_SET
000756197 980__ $$aEBOOK
000756197 980__ $$aBIB
000756197 982__ $$aEbook
000756197 983__ $$aOnline
000756197 994__ $$a92$$bISE