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Cognition and Cognitive Process Modeling

Cognition and Cognitive Process Modeling

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Course Syllabus

  • Name of the Course: Cognition and Cognitive Process Modeling
  • LTP structure of the course: 2-1-1

  • Objective of the course:

    • To provide an overview of cognition in human brain.
    • To introduce students about several AI debates and pro and against arguments of realization of true AI.
    • To provide comprehensive details about the cutting-edge approaches and recent developments of cognitive systems.
    • Introducing students about several cognitive architectures and hand-on working in these architectures.

  • Outcome of the course:

    • Students will get the understanding of how human cognition works as per the explanations till date.
    • Students will get new side of AI development(Using cognitive architectures).
    • Students will get to know the challenges which have been accomplished and which is yet to be addressed to make true AI systems.
  • Course Plan:
ComponentUnitTopics for Coverage
Component 1Unit 1Introduction 
Human Brain: Introduction, cognitive faculties: memory, attention, vision and language, What is cognition, introduction about approaches to cognition, theories of mind: mind - body dualism, materialist theory of mind, identity theory of mind, computational theory of mind.
Unit 2Consciousness and Free Will 
Consciousness: First person approach , third person approach, Chalmers view of consciousness, problem of third person approach, Pattern-Information duality, 
Free Will: Sloman view, free will as continuous dimension, design distinctions for agent modeling.
Component 2Unit 3AI Debates 
First AI Debate: Is AI possible? Pro: Roger Penrose, moravec, Herbert Simon. Artificial mind via symbolic AI, Turing test of AI. Against: Dreyfus five stages of learning, Searle’s chinese room thought experiment, Degrees of understanding, godel’s incompleteness theorem 
Second AI Debate: Connectionist Model, Objectives of Connectionist model, Feldman’s hundred step rules, Brain vs computer model of mind, Lloyd’s cautions, Fodor’s attack, Chamlmers’ defense, Rule based AI.
Unit 4Cognitive Architectures 
ACT-R, CLARION, SOAR, Reinforcement Learning, Distributed Cognition, Learning and Memory Architectures.

Projects 
 

  • Hands-on on cognitive architectures.
  • Analysis of cognition of brain using complex networks.

  • Books:

    • Artificial Mind by Stan Franklin
    • Siegelbaum, Steven A., and A. J. Hudspeth. Principles of neural science. Eds. Eric R. Kandel, James H. Schwartz, and Thomas M. Jessell. Vol. 4. New York: McGraw-hill, 2000.
    • Research papers for brain modeling.