RULES Patty Nordstrom Hien Nguyen

"Cognitive Skills are Realized by Production Rules"

Cognitive Skills Cognitive skills are any mental skills that are used in the process of acquiring knowledge; these skills include reasoning, perception, and intuition. Cognitive skills refer to those skills that make it possible for us to know.

Production Rules Production rules constitute a framework for understanding human cognition Production rules are if-then statements or condition-action pairs Ex. If it snows, then I'll go skiing Ex. If status='OK' and type=3 then count+1

Property of Rules Representation Computational Psychological Practical

Representational Power Represent general information about the world Represent information about how to do things in the world Represent linguist regularities Inferences such as modus ponens

Computational Power Problem solving Searching, space, heuristics Planning Sequence of rule Decision making Learning Acquisition, modification, application Language

Psychological Plausibility Rule-based systems can account for different types of learning –power law of practice –conditioning

Practical Applicability Learning consists of rules so how can this be applied to helping students better acquire rules –Computer tutors –Rule based cognitive systems ACT & ACT-R (Adaptive Control of Thought—Rational) SOAR (Soar is used by AI researchers to construct integrated intelligent agents and by cognitive scientists for cognitive modeling)

Frameworks Frameworks – set of constructs that define important aspects of cognition. Frameworks – cannot make predictions, but you can add assumptions to make theories

Theories Theories still cannot make precise predictions Add assumptions about a specific situation and it is a model of that situation

Models Models - theories with assumptions about its application to a specific situation Many models possible within a theory Production system are theories of human cognition

Cognitive Architectures Cognitive architectures are proposals about the structure of human cognition Cognitive architecture tries to provide a complete, if abstract, specification of a system Production system are theories of human cognition because they are architectures

Features of Production Systems Each production rule is a modular piece of knowledge (a well-defined step of cognition) Complex cognitive processes: –String a sequence of rules –Writing to working memory (goal setting, etc) –Reading from working memory Rules are condition-action asymmetrical Rules are abstract & apply in many situations

How do production systems operate? Pattern matching –Production’s condition vs. contents of working memory Conflict resolution Firing a production -> CYCLE

How to write a production system model? Write a set of production rules to perform the task For AI, production systems are used as programming formalisms –Precise, complete theories of tasks –Without cognitive modeling

Examples A production system for addition Various production system architectures: –PSG: first production system implemented as a computer program –OPS systems Efficient pattern matching and conflict resolution –ACT systems: ACTE, ACT*, ACT-R Include a separate declarative representation –SOAR system

ACT-R A cognitive architecture: a theory about how human cognition works. A framework A cognitive skill is composed of production rules.

ACT-R: Model and Method

ACT-R: Application

ACT-R: Components

Are rules psychologically real? Appropriateness of rules in describing skilled behavior Ability to predict the details of that behavior

Problems Is ACT-R the right production system theory? Assumption: production system framework is the right way to think about cognitive skill.

Implementation Level Problems Algorithm level vs. Implementation level –High-level programming language vs. machine level implementation It is difficult to identify what is going on at the implementation level. –Uniqueness: which implementation is the underlying internal structure? –Discovery: which implementation matches the behavior?

Implementation Level Problems Uniqueness Problem –Neural approach: use neural-like computations Discovery Problem –Rational approach -> ACT-R –Cognition is adapted to environment structure: Memory Categorization Causal inference Problem solving

Intelligent Tutoring Systems Previously –CAI vs. ICAI –Impractical Costly Time No established paradigm for enabling students to acquire knowledge. Now –Cost reduced, advances in AI and cognitive psychology -> shorter time, advances in cognitive science -> instructional design implications

ITS Model knowledge of the domain knowledge of the learner knowledge of teacher strategies gsystem/start.htm

What an ITS must do accurately diagnose students' knowledge structures, skills, and styles diagnose using principles, rather than preprogrammed responses decide what to do next adapt instruction accordingly provide feedback

ACT-based approach to intelligent tutoring Goal structure Instruction in Context Immediacy of Feedback Examples: the Geometry Tutor, the LISP Tutor

Video: Reading Tutor _video_10_min/ _video_10_min/

Question?

Design Scenario In your group, discuss the design of an intelligent tutoring system that teaches HTML to highschool students. Please use the ACT-R cognitive architecture and discuss the use of production rules in your design. FOCUS: –The degree of learner control –Individual vs. collaborative learning –Situated learning –Intelligent Tutor System vs. regular Computer-Aided Instruction

References n/lis06.mpghttp:// n/lis06.mpg eading/li1lk23.htmhttp:// eading/li1lk23.htm ponens-and-modus-tollenshttp:// ponens-and-modus-tollens