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Modeling of Human Decision Making in Problem Solving Based on Physiological Models of Neuron
Shirzadeh, Hossein | 2011
726
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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 41852 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Vosughi Vahdat, Bijan
- Abstract:
- How the human nervous system works is one of the most important topics in science and in this topic providing a model of it is scientists' main concern. The human brain that has been formed from a large number of nerve cells lets it do complex computations. The structure of cognition, memorizing and processing which are some of human features are being studied in many fields of science named "brain and cognitive science".
In this study, we will point to modeling of one of the human cognitive phenomena (decision making in problem solving). In this modeling, we aim to connect the microscopic and macroscopic levels of the nervous system to each other.
First, we will give an introduction of human nervous system, cognitive science and modeling of it. Next, we will classify the different approaches to nervous system modeling and will mention to central issues which must be considered in modeling of nervous system. Then, we will survey three levels (microscopic level, small neural networks and the macroscopic level) of modeling approaches and models presented for each of them and will present our selected model in problem solving at each level.
After that, we will develop modeling of decision making in problem solving with implementing selected models in that three levels and will explain the selected problem (spiral) for this modeling. Finally, we will present the model of decision making and its simulation results to demonstrate that physiological models can be used in psychological models. This is important because lets us do physiological studies on macroscopic level using psychological models based on physiological models of neurons - Keywords:
- Decision Making ; Cognitive Structure ; Neuron Physiological Model ; Small Neural Networks ; Neural System Modeling
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