Full Day Tutorial on Quantum Models of Cognition and Decision Previous Tutorials and Symposia
the Cognitive Science meetings in Nashville
Keywords: classical information processing; quantum information processing; logic and mathematical foundation; Bayesian probability; quantum probability; Markov and quantum processes; quantum entanglement; quantum game theory; conceptual combinations; decision making; memory. General Purpose This full day tutorial is an exposition of a rapidly growing new alternative approach to building computational models of cognition and decision based on quantum theory. The cognitive revolution that
... olution that occurred in the 1960's was based on classical computational logic, and the connectionist/neural network movements of the 1970's were based on classical dynamical systems. These classical assumptions remain at the heart of both cognitive architecture and neural network theories, and they are so commonly and widely applied that we take them for granted and presume them to be true. What are these critical but hidden assumptions upon which all traditional theories rely? Quantum theory provides a fundamentally different approach to logic, reasoning, probabilistic inference, and dynamical systems. For example, quantum logic does not follow the distributive axiom of Boolean logic; quantum probabilities do not obey the disjunctive axiom of Kolmogorov probability; quantum reasoning does not obey the principle of monotonic reasoning. It turns out that humans do not obey these restrictions either, which is why we consider a quantum approach. This tutorial will provide an exposition of the basic assumptions of classical versus quantum theories. These basic assumptions will be examined, side-by-side, in a parallel and elementary manner. The logic and mathematical foundation of classical and quantum theory will be laid out in an accessible manner that uncovers the mysteries of both theories. We will show that quantum theory provides a unified and powerful explanation for a wide variety of paradoxes found in human cognition and decision ranging from attitude, inference, causal reasoning, judgment and decision, conceptual combinations, memory recognition, and associative memory. This tutorial introduces and trains cognitive scientists on this promising new theoretical and modeling approach.