000			05068cam a2200469Ii 4500
001			ocn961930078
003			OCoLC
005			20240726104741.0
008			161102s2016 ii ob 000 0 eng d
040			_aYDX _beng _epn _erda _cYDX _dAZU _dOCLCO _dNT _dIDEBK _dEBLCP _dNT _dSTF _dOCLCQ _dUPM
020			_a9788132236221 _q((electronic)l(electronic)ctronic)
020			_a813223622X _q((electronic)l(electronic)ctronic)
050	0	4	_aHD30 _b.D435 2016
049			_aMAIN
100	1		_aRoy, Sisir, _e1
245	1	0	_aDecision making and modelling in cognitive science /Sisir Roy.
260			_aNew Delhi : _bSpringer, _c(c)2016.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_adata file _2rda
504			_a1
505	0	0	_aForeword; Preface; Contents; About the Author; 1 Introduction; Abstract; 1.1 Various Aspects of Decision Making; 1.2 Emotion, Logic and Decision Making; References; 2 Various Approaches to Decision Making; Abstract; 2.1 Decision Making (On the Basis of Human Decisions); 2.1.1 Canonical Approach and Normative Models; 2.1.2 The Axiomatic Approach; 2.1.3 Bayesian Probabilistic Approach; 2.1.4 Bayesian Statistics; 2.1.5 Bayes' Rule; 2.2 Decision Making and Statistical Inference; 2.2.1 Bayesian Probability and Cognitive Domain; 2.3 Dempster-Shafer Theory.
505	0	0	_a2.3.1 Cognition and Emotion in Human Decision MakingReferences; 3 Predictability of Brain and Decision Making; Abstract; 3.1 Prediction and Movement; 3.2 How Does the Brain Predict?; 3.2.1 Motor Binding in Time and the Centralization on Prediction; 3.2.1.1 Pulsatile Motor Control System; 3.3 How Can a Neuronal Circuit Predict?; 3.4 Dynamic Geometry and Bayesian Approach to Decision Theory; References; 4 New Empirical Evidences on Decision Making and Cognition; Abstract; 4.1 Disjunction Effect; 4.2 Categorization-Decision Interaction; 4.3 Perception of Ambiguous Figures.
505	0	0	_a4.4 Conjunction and Disjunction Fallacies4.5 Over Extension of Category Membership; 4.6 Over-Distribution Effect in Memory Recognition; 4.7 Failures of Commutativity in Decision Making; 4.7.1 Non-commutativity and the Uncertainty Principle Underlying the Functional Architecture of the V1 Cortical Area; 4.7.2 Architecture of VI Area; 4.8 Uncertainty Relation and Ambiguity in Perception; 4.9 Uncertainty Relations for Unsharp Observables; 4.10 Wave-Particle Dualism and Double Slit Experiment; References; 5 Fundamental Concepts of Mathematics and Quantum Formalism; Abstract; 5.1 Postulates.
505	0	0	_a5.2 Mathematical Preliminaries5.2.1 Vector Space; 5.2.2 Subspaces; 5.2.3 Norms; 5.2.4 Scalar Product; 5.3 Hilbert Space; 5.3.1 Hermitian Operator; 5.3.2 Unitary Operator; 5.4 Commutative Properties; 5.4.1 Projection Operator; 5.5 Projection Postulate (PP); 5.5.1 Statement of Projection Postulate (PP); 5.6 Unsharp Observable and Operational Quantum Theory; 5.7 Stern-Gerlach Experiment; 5.8 POVM for Spin-Half Particles; References; 6 The Complementary Principle, Concept of Filter and Cognition Process; Abstract; 6.1 Spatiotemporal Representation of Image.
505	0	0	_a6.2 The Response-Percept Domain and Observation Process6.3 The Complementarity Principle, Percepts and Concept; References; 7 Quantum Probability Theory and Non-Boolean Logic; Abstract; 7.1 Logic and Cognition; 7.2 Logic and Decision Making; 7.3 Boolean Algebra; 7.4 Quantum Logic and Non-Boolean Algebra; 7.4.1 Propositional Logic; 7.4.2 Lattices; References; 8 Quantum Ontology and Context Dependence; Abstract; 8.1 Newton and Metaphysics; 8.2 Quantum Ontology; References; 9 Modern Neuroscience and Quantum Logic; Abstract; References.
520	0		_aThis book discusses the paradigm of quantum ontology as an appropriate model for measuring cognitive processes. It clearly shows the inadequacy of the application of classical probability theory in modelling the human cognitive domain. The chapters investigate the context dependence and neuronal basis of cognition in a coherent manner. According to this framework, epistemological issues related to decision making and state of mind are seen to be similar to issues related to equanimity and neutral mind, as discussed in Buddhist perspective. The author states that quantum ontology as a modelling tool will help scientists create new methodologies of modelling in other streams of science as well.
530			_a2 _ub
650		0	_aDecision making.
650	1	4	_aPsychology.
650	2	4	_aPsychometrics.
650	2	4	_aMethodology of the Social Sciences.
650	2	4	_aQuantum Physics.
650	2	4	_aOperation Research/Decision Theory.
655		1	_aElectronic Books.
856	4	0	_zClick to access digital title | log in using your CIU ID number and my.ciu.edu password. _uhttpss://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=1331315&site=eds-live&custid=s3260518
942			_cOB _D _eEB _hHD. _m2016 _QOL _R _x _8NFIC _2LOC
994			_a92 _bNT
999			_c77059 _d77059
902			_a1 _bCynthia Snell _c1 _dCynthia Snell