1. 고려대학교 산업공학과 IND 643 Cognitive Engineering 1. Introduction  Divide-and-conquer strategy  Allen Newell (1973) – unified theory, production system  ACT-R, 3CAPS, EPIC, Soar

2. 고려대학교 산업공학과 IND 643 Cognitive Engineering A Brief Sketch of ACT-R  declarative knowledge  chunks followed by slots and values  procedural knowledge  production rules – condition-action pairs  each production as a basic step of cognition  display the significance of goal structures

3. 고려대학교 산업공학과 IND 643 Cognitive Engineering No-Magic Doctrine in ACT-R 1. Experimentally Grounded 2.Detailed and Precise Accounting of Data 3.Learnable Through Experience 4.Capable of Dealing with Complex Cognitive Phenomena 5.Principled Parameters 6.Neurally Plausible

4. 고려대학교 산업공학과 IND 643 Cognitive Engineering 2. knowledge Presentation

5. 고려대학교 산업공학과 IND 643 Cognitive Engineering Procedural-Declarative Distinction  long-term repository of procedural knowledge in the form of production rules  parallel, long-term, declarative repository  hippocampal for declarative knowledge  basal ganglia for procedural knowledge

6. 고려대학교 산업공학과 IND 643 Cognitive Engineering Structure of Chunks  independent patterns of info as the sets of slots with associated values  types of pattern – isa slot  two chunks origins – goals & objects  two styles of slot structures but syntactically identical and identically processed

7. 고려대학교 산업공학과 IND 643 Cognitive Engineering Production Rules  General Features  basic structure of a production goal condition + chunk retrieval --> goal transformations  Conflict Resolution

8. 고려대학교 산업공학과 IND 643 Cognitive Engineering Production Rules  Four claims with the use of Production Rules 1. Modularity 2. Abstraction 3.Goal Factoring 4.Conditional Asymmetry

9. 고려대학교 산업공학과 IND 643 Cognitive Engineering Production Rules  Production Syntax  the condition  a goal chunk followed by other chunk patterns for retrievals from memory  action for creating and modifying goal chunks  =, >

10. 고려대학교 산업공학과 IND 643 Cognitive Engineering Production Rules  Restrictions on Production Rules  chunk retrieval not in the initial selection of production rules  goal modifications on the right-hand side of a production  drastic reduction in the size of production conditions

11. 고려대학교 산업공학과 IND 643 Cognitive Engineering Goal Structures/ Production Rules  Goal Structures in ACT-R  creates a natural seriality to cognition  parallelism at the subsymbolic level 1.how to be any interrupt-driven cognition 2.how to pursue multiple goals in parallel 3.perfect-memory assumptions

12. 고려대학교 산업공학과 IND 643 Cognitive Engineering Types of Production Rules  goal match, declarative retrieval, goal transformation  6 production types 1. No Change (No Stack Change, No Goal Modification) 2. Goal Elaboration (No Stack Change, Goal Modification)

13. 고려대학교 산업공학과 IND 643 Cognitive Engineering Types of Production Rules 3. Side Effect (Push on Stack, No Goal Modification) 4. Return Result (Push on Stack, Goal Modification) 5. Pop Unchanged (Pop Stack, No Goal Modification) 6. Pop Changed (Pop Stack, Goal Modification)

14. 고려대학교 산업공학과 IND 643 Cognitive Engineering 3. Performance

15. 고려대학교 산업공학과 IND 643 Cognitive Engineering Conflict Resolution  deciding which production to fire  productions in conflict set are ordered by expected gain  Expected Gain = E = PG – C  No production with positive expected utility, the goal is popped with failure

16. 고려대학교 산업공학과 IND 643 Cognitive Engineering Conflict Resolution  Role of P, G, and C  P = qr  C= a + b  a = sum of the match time = 0.05 sec  Little to say about the initial value of G  However, once the value of a goal is set, ACT-R does have something to say

17. 고려대학교 산업공학과 IND 643 Cognitive Engineering Conflict Resolution  Stochasticity  noise from a logistic distribution introduce some stochasticity  probability of selecting a production

18. 고려대학교 산업공학과 IND 643 Cognitive Engineering Conflict Resolution  Evidence: “Probability Matching”  probability-learning paradigm  choice probability – undermatching

19. 고려대학교 산업공학과 IND 643 Cognitive Engineering Retrieval  Activation-Based Retrieval   Base-Level Activation B i  how recently and frequently accessed  Source Activations W j  attention given to elements of the goal

20. 고려대학교 산업공학과 IND 643 Cognitive Engineering Retrieval  Strengths of Association S ji  how often the chunk i was needed when j was an element of the goal  Changes in Base-Level Activation  B(t) = β- d ln(t) + ε 1 + ε 2

21. 고려대학교 산업공학과 IND 643 Cognitive Engineering Retrieval  Relationship to Response Probability  Probability of a successful retrieval  Odds of recall decreases as a power function of time  odds of recall = Prob/(1-prob) 

22. 고려대학교 산업공학과 IND 643 Cognitive Engineering Retrieval  Partial Matching  M ip = A i – D ip  Relationship to Latency 

23. 고려대학교 산업공학과 IND 643 Cognitive Engineering Retrieval  The Fan Experiment  fan – the number of facts studied about a concept  foil – recombinations of persons and locations  latency increases with number of facts about persons and locations  decrease in associative strength with fan  subjects generally slower to reject foils