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Jim Staszewski Department of Psychology Carnegie Mellon University

Cognitive Models of Human Expertise and their Scientific and Practical Value. Jim Staszewski Department of Psychology Carnegie Mellon University. AAAI Fall Symposium Biologically Inspired Cognitive Architectures Arlington, VA 8 November 2008. Overview.

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Jim Staszewski Department of Psychology Carnegie Mellon University

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  1. Cognitive Models of Human Expertise and their Scientific and Practical Value Jim Staszewski Department of Psychology Carnegie Mellon University AAAI Fall Symposium Biologically Inspired Cognitive Architectures Arlington, VA 8 November 2008

  2. Overview Cognitive Architectures and Human Expertise Computational Models of Human Expertise Practical Utility of Expert Models Closing Points

  3. Cognitive Architectures and Human Expertise Scientific Relevance Expert performance lies at the frontiers of human adapation/intelligence. It represents the (current) endpoint of the path of learning. Cognitive architectures seek general, comprehensive theories of intelligence. So, expert performance and its acquisition represent modeling targets for unified, integrative theories of intelligence, i.e., cognitive architectures. Engineering Relevance “Reverse engineering” expert skills in problem domains resistant to computational solutions represents a viable analogical strategy for algorithm discovery.

  4. Computational Models of Human Expertise Domain DataMedium Capability Memory/Digit Span1 Long. EPAM* Performance & Learning Mental Calculation/Multiplication2 Long. Lisp Performance Problem Solving/Rubik’s Cube3 X-Sect SOAR* Performance 1 Richman, Staszewski, & Simon, 1995; Staszewski, 1993 2 Staszewski, 1988 3 Staszewski, 1990

  5. Domain-independent Mechanisms • Perceptual pattern recognition mediated by chunked conceptual knowledge • Retrieval structures: Hierarchical data structures for indexing info in memory, used for rapid and reliable storage and retrieval of ordinal information

  6. Exceptional Span Normal 7±2 DD SF

  7. 104 Random Digits 70364746158952171155233090365415510502437703742355229858427897634969443998594167528292668853520435166615

  8. DD’s Encoding/Retrieval Structure for 100 Digits 7036 4746 1589 5217 115…. 3k 10m 1/2m 1m Age

  9. Content CategoryExample 1/4 m 497 1/2 m 142 3/4 m 315 1m 420 3k 716 2m 928 3m 1430 10k 2904 10m 4753 Date 1800 Age 284 Misc. 987 StructureExample Three-digit groups Time 4:20 Time+decimal 46.3 Age+decimal 79.9 “0”+time 049 “0”+age 063 Misc. pattern 111 Four-digit groups Time 49:27 Time+decimal 6:30.7 Age+age 8785 “0”+three-digit code 0799 Misc. pattern 8642 Misc. pattern+decimal 135.9 DD’s Semantic Knowledge Base for Digit Group Chunking

  10. Problem Sizes For Mental Calculation Study Problem ClassExample 1 x 1 8 x 6 1 x 2 4 x 37 1 x 3 7 x 958 1 x 4 9 x 4,474 1 x 5 3 x 34,586 2 x 2 52 x 76 2 x 3 65 x 741 2 x 4 78 x 6,294 2 x 5 83 x 81,303

  11. Performance Gains for GG with 4 Years of Practice Initial 30 Sessions Solution Times (in seconds) Final 30 Sessions Problem Size 180 Initial Oral 160 Initial Visual 140 Final Oral Final Visual 120 100 80 60 40 20 0 1x1 1x2 1x3 1x4 1x5 2x2 2x3 2x4 2x5

  12. GG’s Solution Times for Orally Presented 2x Problems

  13. Multiplicand Partial Product 1 6 8 6 3 3 1 - Multiplier Partial Product 2 9 4 7 6 2 5 9 3 0 5 0 3 6 Mechanisms • Retrieval structures problem components and intermediate results • Recognition of larger subproblems whose products are directly retrieved • Computational strategies that minimize memory loads

  14. Expert Problem Solving Expert Problem Solving Performance: 100% Success Rate Solution Time: X = 42.4 SD = 12.6 sec Operations: X = 70.1 SD = 21.6

  15. Expert’s Retrieval/Goal Structure BLUE WHITE MIDDLE FACE FACE SLICE WHITE CORNERS WHITE EDGES POSTION & ORIENT CORNERS POSTION & ORIENT EDGES & CORNER POSTION ORIENT EDGES & ALIGN SLICES POSTION CORNERS ORIENT CORNERS POSTION & ORIENT CORNERS R- U- R+ (ry) L2 u+ L2 U- L- U+ (wy) R- (yb) U2 L+ ………………………………V- U2 V2 U+ R- U- V2 V+ U- R+ (by) D+ START FINISH

  16. Perceptual Chunks for Triggering Macros Problem State Expert’s Perceptual Focus Trigger state for executing macro-operator for orienting White Corners Trigger state for executing macro-operator for orienting Middle Slice Edges

  17. Macro-operator for positioning White Corners Macro-operator for orienting Middle Slide Edge Cubes F+ D- F- R- D- R+ R- D+ R+ F+ D+ F- U+ U- U2 V+ U- V+ U- V+ U2 V- U- V- U- V- U2 Macro-operator Organization

  18. Utility of Expert Models Genome Map : Genetic Engineering :: Expert Model : Cognitive Engineering?

  19. Expert Model Based Training Programs: AN/PSS-12 and PSS-14

  20. Anti-Tank (AT) & Anti-Personnel (AP) Landmines AT-M AT-LM AP-M AP-LM-S AP-LM-L

  21. M19 VAL69 M14 M14 M14

  22. PSS-12 Experimental Training Effects

  23. Impact • CENTCOM sponsors training of 5th SOG troops on CEBES PSS-12 techniques for • training of indigenous humanitarian deminers in Jordan, Eretria, Djbouti • AMC-FAST sponsors installation of permanent JRTC training site and trainer training for 519th MP BN and 10th MTN DIV 41st EN BN deploying to Kosovo • 41st Combat EN BN trains 6 sapper platoons for Bosnia deployment • 326th EN BN 101st Airborne trained prior to Iraqi Freedom deployment • US Army adopts CEBES PSS-12 training and techniques • Colombian Army adopt CEBES PSS-12 training and techniques • Soldiers given CEBES training currently use the PSS-12 in countermine operations in Iraq, Afghanistan, Colombia, and elsewhere.

  24. Original Operator Training vs Expert Model Based Training

  25. AT-M AP-M (excluding VS50) 10.21” 23.6” AT-LM AP-LM-L 2.63” 2.26” AP-LM-S 2.34” Operator Heading:

  26. U.S. Army Combat Engineer with PSS-14 near Bagram Airport, Afghanistan, April 2004 Impact • HSTAMIDS development program granted reprieve and continued • Pre-production PSS-14 and training deployed to support OEF in Afghanistan • Army distribution policy ties training to equipment • USAES operational test of production units yields 98.7% detection rate • PSS-14 and training deployed to support Operation Iraqi Freedom • U. S. soldiers given CEBES training currently use the PSS-14 in countermine operations in Iraq and Afghanistan • US Humanitarian Demining Program employs CEBES approach for operator training • Research on signal processing algorithms incorporates spatial information • Robotic system under development searches for expert patterns

  27. Closing Points • Cognitive architectures of comprehensive scope should explain expert performance and its development • Data resources appropriate for modeling are limited, but… -- Some exist -- Methods for analyzing expertise work in the lab and the field…more on the way • Modeling expertise can generate practical solutions to difficult, high-stakes problems and thus serve public interests

  28. Questions?

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