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A Stochastic Graph Grammar Algorithm for Interactive Search

A Stochastic Graph Grammar Algorithm for Interactive Search. Rahul Rai Assistant Professor Department of Mechanical Engineering California State University at Fresno Fresno, California 93740 rarai@csufresno.edu. Tolga Kurtoglu Research Scientist Mission Critical Technologies

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A Stochastic Graph Grammar Algorithm for Interactive Search

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  1. A Stochastic Graph Grammar Algorithm for Interactive Search Rahul Rai Assistant Professor Department of Mechanical Engineering California State University at Fresno Fresno, California 93740 rarai@csufresno.edu Tolga Kurtoglu Research Scientist Mission Critical Technologies Intelligent Systems Division NASA Ames Research Center Moffett Field, California 94035 tolga.kurtoglu@nasa.gov Matthew I. Campbell  Associate Professor Automated Design Laboratory Department of Mechanical Engineering University of Texas at Austin Austin, Texas 78712-0292 mc1@mail.utexas.edu

  2. Introduction • generative grammars is a powerful approach to represent different topologies, configurations or shapes within a single search space • approaches the representational capacity of human designers that create and compare wildly different solutions during the conceptual design phase • We are interested in how grammars can be used to interactively guide human designers or even automatically find promising concepts • grammars merely define a space or tree of solutions • not a means to search this space • search trees -- intractably large set of solutions • Need some way to evaluate concepts • target specific areas of the tree that best meet the designer’s expectations. • Evaluation completely left to humans • Difficult on concepts when no dimensions are provided

  3. Approach • present a sample of solutions to the designer • Get feedback • use that information to find better solutions in the search tree • seeks solutions to maximize the designer’s preference • reflecting the user input onto the generative grammar rules • which rule • combination of rules • ordering of rules • time to execute a particular rule …leads to the best design

  4. Seed Rules for necktie knot grammar In order to begin any tie knot a triangular basis has to be created. This beginning move creates three regions L C R (Left, Center, Right). This gives rise to seed rules. One can begin in two way Li and Lo (i denotes in plane and o denotes out plane).

  5. Continuing rules for tie knot • One can continue from the seed rule by implementing one of the six rules shown here • There are two restriction on continuing rules. • First, the i and o has to alternate • Second, next step cannot have same basis, i.e., if previous step is L then next step has to be either C or R.

  6. Terminating rules for tie knots • A tie knot can only terminate in one of the possible two ways shown above. • T denotes (termination and no more rules can be applied)

  7. 18 graph grammar rules for tie knots • Based on initiation, continuing, and terminating aspects of tie knot, only 18 graph grammar rules can be deduced for the tie knot problem. The rules code in graphsynth are as follows: Rule 1 LHS Lo RHS LoRi Rule 2 LHS Lo RHS LoCi Rule 3 LHS Ri RHS RiCo Rule 4 LHS Ri RHS RiLo Rule 5 LHS Co RHS CoLi Rule 6 LHS Co RHS CoRi

  8. Rule 11 Rule 7 LHS Li RHS LiCo Rule 12 Rule 8 LHS Li RHS LiRo Rule 13 Rule 9 LHS Ro RHS RoCi Rule 14 Rule 10 LHS Ro RHS RoLi Rule 15 Rule 11 LHS Ci RHS CiRo Rule 16 Rule 12 LHS Ci RHS CiLo Rule 17 (Initiation ) Rule 13 LHS Null RHS Li Rule 18 (Initiation ) Rule 14 RHS Lo LHS Null Rule 15 Rule 19 (Termination ) RHS CoT LHS Co

  9. 4 A green number denote that rule selected for application among applicable rules Vertex where to apply a rule in the LHS of a step Four in hand knot Step 1 Li Seed graph (Null) Applicable Rules 13, 14 Step 2 Li Li Ro Applicable Rules 7, 8 Step 3 Li Ro Li Ro Li Applicable Rules 9, 10 Step 4 Li Ro Li Li Ro Li Co Applicable Rules 7, 8 Step 5 Li Ro Li Co Li Ro Li Co T Applicable Rules 5, 6, 15

  10. 4 A green number denote that rule selected for application among applicable rules Vertex where to apply a rule in the LHS of a step Step 1 Cross knot 1 Li Seed graph (Null) Applicable Rules 13, 14 Step 2 Li Ro Li Applicable Rules 7,8 Step 3 Li Ro Li Ro Ci Applicable Rules 9, 10 Step 4 Li Ro Ci Li Ro Ci Ro Applicable Rules 11,12 Step 5 Li Ro Ci Ro Li Ro Ci Ro Applicable Rules 9,10 Li

  11. Cross knot 2 Step 6 Li Ro Ci Ro Li Ro Ci Ro Applicable Rules 7,8 Co Li Li Step 7 Li Ro Ci Ro Li Ro Ci Ro Applicable Rules 5, 6, 15 Co Li T Co Li

  12. 4 A green number denote that rule selected for application among applicable rules Vertex where to apply a rule in the LHS of a step Step 1 Windsor 1 Li Seed graph (Null) Applicable Rules 13, 14 Step 2 and 3 Step 2 Li Co Li Applicable Rules 7,8 Step 3 Li Co Li Co Li Applicable Rules 5, 6, 15 Step 4 Li Co Li Ro Li Co Li Applicable Rules 7,8 Step 5 Li Co Li Ro Li Co Li Ro Ci Applicable Rules 9,10

  13. Windsor 2 Step 6 Li Co Li Ro Ci Applicable Rules 11, 12 Li Co Li Ro Ci Ro Step 7 Li Co Li Ro Ci Ro Applicable Rules 9,10 Li Co Li Ro Ci Ro Li Step 8 Li Co Li Ro Ci Ro Li Applicable Rules 7,8 Li Co Li Ro Ci Ro Li Co Step 9 Li Co Li Ro Ci Ro Li Co Applicable Rules 5,6,15 Li Co Li Ro Ci Ro Li Co T

  14. 4 A green number denote that rule selected for application among applicable rules Vertex where to apply a rule in the LHS of a step Small knot Step 1 Lo Seed graph (Null) Applicable Rules 13, 14 Step 2 Lo Lo Ri Applicable Rules 1, 2 Step 3 Co Lo Ri Lo Ri Applicable Rules 3, 4 Step 4 Co T Lo Ri Co Lo Ri Applicable Rules 5 ,4, 15

  15. T31 T24 Maximum of Nine Steps(85solutions) T32 Co T43 Co T30 T28 Co T33 Co T37 Co T9 Co Ri Ri T48 Co Ri Co Li Li T25 Co Ri T20 Li Co Li Co Ri T10 Lo Co Co Lo Ro Li Ro Ro Li Lo T53 T3 T7 Ro Lo T29 Ri Ri Co Ci T40 Ro Li Co Co Li Ri Co T27 Li Co Ci Ro Lo Co Ri Co Ro Li Ri Co Li Lo Li Lo Ro Ro Ci T13 T39 Ci Ri Li T46 Co Co T1 Co Li Ro Ri Ro Li Ro Lo Li T12 Co Ro Co T35 Li Ri Ci Co Co Lo Ri Ri Lo Ri Lo Co T54 Ci Ro Li Ri Lo Ci T19 Co Li Ro Co Ci T51 Lo Ri Lo Co Ri Ri Lo Ri Lo Ri T4 T Ri Co Co Lo Li T23 T5 Co Lo Ri Li Co Lo Ri Ro Li T38 Co Lo Co Ci Ri T42 T2 Ci Ro Ri Ci Co Co Lo Ro T26 Li T16 Ci Ro Ci Ci Lo T11 Co Lo Ri Ro Lo Li Li Ri Ro Ri Ro Li Ri T17 Co Li Ci Lo Ci Co Co Ro Li Co Lo Co Ri Co T47 T8 Lo Co Li Ri Co Co T41 T45 Ro Co Lo Ri Co T6 Lo Ro Co T44 T14 T55 Ri Li Li Ri Co T52 T22 T15 Co Co T49 Co Co T50 T34 T57 T36 T58

  16. title: “A Stochastic Graph Grammar Algorithm for Interactive Search” • the tree is never explicitly represented • large and difficult to visualize • may easily contain more states than the computer can store • 1010 =9.3 TB if each state in only one kilobyte • However, the number of rules that lead to these solutions is often a small and manageable size • grammar rules represent heuristics or constraints provided by experts in the particular design domain • grammar rules make definitive changes to a particular concept and their use is often clearly discernible within the final candidate solution • makes sense to gather statistics on the rules used to navigate the search tree • In the necktie grammar, rules define shape and size of the knot.

  17. Stochastic Process rule7 rule3 rule1 rule6 • any given state in the tree, a set of options is determined

  18. rule7 rule3 rule1 rule6 B named for G.E.P. Box. First to coin the phrase “exploration vs. exploitation” B = [0 1]

  19. rule7 rule3 rule1 rule6

  20. Recreate the Cross-Knot • Go all the way to 15th level of tree (5461 candidates) • Calculate difference from cross-knot

  21. Results After reviewing 30 out of 5461 solutions, we find a solution in 98 percentile.

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