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[Knowledge-based AI] {ud409} Lesson 6: 06 - Production Systems

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This example is adapted from the following paper: Lehman, J. F., Laird, J. E., Rosenbloom, P. S. (1996). A gentle introduction to Soar, an architecture for human cognition. Invitation to Cognitive Science , 4 , 212-249. David is using his k

 

 

 

 

 

 

 

This example is adapted from the following paper:

Lehman, J. F., Laird, J. E., & Rosenbloom, P. S. (1996). A gentle introduction to Soar, an architecture for human cognition. Invitation to Cognitive Science4, 212-249.

 

 David is using his knowledge to make a decision.

  • How is he using his knowledge to make a decision?
  • What is the architecture?
  • what is the reasoning that leads him to make that specific decision?

 

 

 

 Function of a Cognitive Architecture

Production Systems:
Winston Chapter 7, pages 119-137 can be found at:http://courses.csail.mit.edu/6.034f/ai3/rest.pdf 

 

 

 

 Levels of Cognitive Architectures

 

 

 

 

 

 

 

 Assumptions of Cognitive Architectures

 

This list is adapted from the following paper:

Lehman, J. F., Laird, J. E., & Rosenbloom, P. S. (1996). A gentle introduction to Soar, an architecture for human cognition. Invitation to Cognitive Science4, 212-249.

 

 

 

 

Architecture + Content = Behavior 

 

 

 

 

 

 A Cognitive Architecture for Production Systems

A general architecture of Cognitive system

 

Next is a specific kind of Cognitive system: SOAR

 

This example is adapted from the following paper:

Lehman, J. F., Laird, J. E., & Rosenbloom, P. S. (1996). A gentle introduction to Soar, an architecture for human cognition. Invitation to Cognitive Science4, 212-249.

 

Here we first only focus on the deliberation of SOAR => long-term memory and working memory

Thre are three parts of knowledge in long-term memory:

  • Procedural: how to do certain things
  • Sematic: generalization in the form of concepts and models of the world
  • Episodic: events, eg. what happened yesterday

 

 

 

 Return to the Pitcher

 

 

 

 Action Selection

 

decision making => find a path from S0 to S101 => havent perform any action, just thinking

 (comment: model predictive control?)

 

 

 Putting Content in the Architecture

 

simple representation of information

 

 

 

 Bringing in Memory

 

 production rules:

 

 

 

 Exercise: Production System in Action I

left: situation; right: knowledge (rules)

 

r2 => end

r2 => r4 => r5 => end

 

r2 => r4 => r5 & r6 => conflict 

 

 

 

 Chunking

 

r2 => r4 => r5 & r6 => conflict => learn to choice r5 or r6 here

 

here, reasoning, learning and memory are closely connected.

 

 

 

 

 

 

 

 

 

Fundamentals of Learning

 

 reason first, if reach an impasse, turn back to learning

We are trying to build a unified theory of reasoning, memory and learning, where the demands of memory and reasoning constrain the processing of learning 

 

 

 

 

 

 

 

 

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