Course #3 :Schema and Child Concept Acquisition:

Intuition initially sparse nodes of concepts and as the knowledge gets added nodes gets close and acts as a semi-symbolic concepts.

Course: Schemas in Problem solving

Instructor: Sandra P Marshall

Lec1: Fundamentals

  • Schema roots
  • The nature of schema
  • The Schemas of arithmetic story problem

Lec2: Schemas and Instruction

  • Theoretical issues for instruction
  • The story problem solver
  • The problem-solving environment

Lec3: Learning from Instruction

  • Learning and schema theory
  • Learning from schema-based instruction
  • The acquisition of planning knowledge

Lec4: Schemas and Assessment

  • Schema-based assessment
  • Assessment in SPE and PSE

Lec5: Schemas and Models

  • Rule-based production systems.
  • Neural networks
  • Hybrid models
  • The performance model
  • The Learning model
  • The full schema model

Coda

very interesting and very insightful. a good start to know how humans acquire knowledge. Moreover this theory also gives insight to how logic and probability bring two school of thoughts (Classical and Modern AI) together.

 

 

 

Games with Imperfect Information

Part 1 and  Chapter 3:

 

3.1 Varieties of knowledge in games

  • Perfect information
  • Imperfect information

3.2 Imperfect information games at a glance

3.3 Modal-epistemic logic

  • Process graphs with uncertainty
  • Model epistemic language
  • Iterations and group knowledge
  • Uniform strategies and non-determinacy

3.4 Correspondence for logical axioms

  • Correspondence analysis of special axioms
  • general logical methods

3.5 C