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Developing a Visualization Tool for Spider Web-Building Algorithms 模擬蜘蛛結網之演算法設計及視覺化工具開發

Developing a Visualization Tool for Spider Web-Building Algorithms 模擬蜘蛛結網之演算法設計及視覺化工具開發. 指導教授：尹邦嚴 陳怡孜 陳瑩哲 沈扇綸 郭怡君. Outline. Introduction Abstract Motivation Literature review Artificial Intelligence Related spider papers Spider web-building algorithm design

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Developing a Visualization Tool for Spider Web-Building Algorithms 模擬蜘蛛結網之演算法設計及視覺化工具開發

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  1. Developing a Visualization Tool for Spider Web-Building Algorithms模擬蜘蛛結網之演算法設計及視覺化工具開發 指導教授：尹邦嚴 陳怡孜 陳瑩哲 沈扇綸 郭怡君 OPlab, IM, NTU

  2. Outline • Introduction • Abstract • Motivation • Literature review • Artificial Intelligence • Related spider papers • Spider web-building algorithm design • Visualization tool prototype of the model • Internal factors • External factors • Conclusion and future work OPlab, IM, NTU

  3. I. Introduction 1/2 • Abstract • Sequential behavior of spider web-building model • Internal factors of the spider web-building model • External factors of the spider web-building model • Implementation of visualization tool OPlab, IM, NTU

  4. I. Introduction 2/2 • Motivation • Figure 1. The motivation of the model OPlab, IM, NTU

  5. Outline • Introduction • Abstract • Motivation • Literature review • Artificial Intelligence • Related spider papers • Spider web-building algorithm design • Visualization tool prototype of the model • Internal factors • External factors • Conclusion and future work OPlab, IM, NTU

  6. II. Literature review1/3 • Artificial Intelligence • Swarm intelligence • Geese migratine –fly in a “V” formation • Bees and wag-tail dance • Ant colony optimization (ACO) Solve discrete optimization problems (Dorigo, 1992) • Particle swarm optimization (PSO) A optimization for representing sociocognition of human and artificial agents tool (Kennedy and Eberhart,1995) OPlab, IM, NTU

  7. II. Literature review 2/3 • Related spider papers • Influence of the genes on the web (Kirnk, 1996) • Wind, Temperature, and Humidity (Vollrath, 1997) • Prey size (Vollrath, 1998) • The pattern of the capture spiral(李蔡彥and林翰儂, 2004) OPlab, IM, NTU

  8. II. Literature review 3/3 • Related spider artificial intelligence • The pattern of the capture spiral (李蔡彥and林翰儂, 2004) Figure.2 Capture spiral pattern Figure.3 Different capture spiral pattern OPlab, IM, NTU

  9. Outline • Introduction • Abstract • Motivation • Literature review • Artificial Intelligence • Related spider papers • Spider web-building algorithm design • Visualization tool prototype of the model • Internal factors • External factors • Conclusion and future work OPlab, IM, NTU

  10. III. Spider web-building algorithm model design 1/8 Figure.4 The factor-analysis tree of web-building. OPlab, IM, NTU

  11. III. Spider web-building algorithm model design 2/8 Figure.5 The rule-analysis tree of web-building. Auxiliary spiral (AS) Capture spiral (CS) Figure.6 The real spider web.Influence of the genes on the web (Kirnk, 1996) OPlab, IM, NTU

  12. Radii Gene 1：Control the number of radii () and base angle (). Gene 2：Control the difference of the angle () from the north to the first radii. Gene 3：Control the difference of the angle () between the other radii. III. Spider web-building algorithm model design 3/8 Figure.7 The relation between radii and gene OPlab, IM, NTU

  13. III. Spider web-building algorithm model design 4/8 • Frame The distance (HF) between hub and frame is the length of the radii (RL) subtract the length which is control by Gene 4 (). HF = RL - Because of the effects of the gravity, the distance between hub and downward frame is longer than the others distance. RL HF Figure.8 The relation between frame and gene OPlab, IM, NTU

  14. III. Spider web-building algorithm model design 5/8 • AS The effects of the interactions between Gene 5 () and Gene 6 () control the intersection points of the AS and radii, resulting in a clockwise spiral (AS). Figure.9 The relation between AS and gene OPlab, IM, NTU

  15. III. Spider web-building algorithm model design 6/8 • CS Along the AS, a spider creates an anticlockwise spiral (CS). The intersection points of the CS and radii are effected by Gene 7 (). Figure.10 The relation between CS and gene OPlab, IM, NTU

  16. CS reverse Using reverse to fill the remaining space of web, which is uncovered with CS. III. Spider web-building algorithm model design 7/8 Figure.11 The relation between radii and gene OPlab, IM, NTU

  17. III. Spider web-building algorithm model design 8/8 • Experiments Figure.12 Sequential behavior of spider web-building. OPlab, IM, NTU

  18. Outline • Introduction • Abstract • Motivation • Literature review • Artificial Intelligence • Related spider papers • Spider web-building algorithm design • Visualization tool prototype of the model • Internal factors • External factors • Conclusion and future work OPlab, IM, NTU

  19. IV. Visualization tool prototype of the model 1/23 • Internal factors • Explanation of the rules • Experiments • Model simulation • Verification • External factors • Explanation of the rules • Experiments • Model simulation • Verification OPlab, IM, NTU

  20. IV. Spider web-building algorithm model design 2/12 • Internal factors Figure.6 The internal factor-analysis tree of web-building OPlab, IM, NTU

  21. IV. Visualization tool prototype of the model 3/23 • Internal factors • Body size (χ) Larger spiders would build larger webs • Weight (ψ) Heavier spiders with the same size of their body would build larger webs • Gland silk (ω) Larger gland silk with the same size of their body build larger webs • χ, ψ, ω interaction OPlab, IM, NTU

  22. Figure.13(a) minimize χ, ψ, ω Figure.13(b) Maximize χ, minimize ψ, ω IV. Visualization tool prototype of the model 3/23 • Body size (χ) • experiments • Model simulation • Verification OPlab, IM, NTU

  23. Figure.14(a) minimize χ, ψ, ω Figure.14(b) Maximize ψ, minimize χ, ω IV. Visualization tool prototype of the model 4/23 • Weight (ψ) • experiments • Model simulation • Verification OPlab, IM, NTU

  24. Figure.15(b) Maximize ω, minimize χ, ψ Figure.15(a) minimize χ, ψ, ω IV. Visualization tool prototype of the model 5/23 • Gland silk (ω) • experiments • Model simulation • Verification OPlab, IM, NTU

  25. Figure.16(b) Maximize ω, χ, ψ Figure.16(a) minimize χ, ψ, ω IV . Visualization tool prototype of the model 6/23 • χ, ψ, ω interaction experiments • experiments • Model simulation • Verification OPlab, IM, NTU

  26. IV. Visualization tool prototype of the model 1/23 • Internal factors • Explanation of the rules • Experiments • Model simulation • Verification • External factors • Explanation of the rules • Experiments • Model simulation • Verification OPlab, IM, NTU

  27. IV. Visualization tool prototype of the model 7/23 • External factors • Climate • Surrounding environments • Prey size Figure.17 The external factor analysis tree of web-building OPlab, IM, NTU

  28. IV. Visualization tool prototype of the model 8/23 • Climate • Wind • Affect mesh • Affect the length and the number of radius • Temperature • Affect mesh • Affect the frequency of CS reverse • Humidity • Affect mesh • Affect the viscosity of CS OPlab, IM, NTU

  29. IV. Visualization tool prototype of the model 9/23 • Wind( ) • experiments • Model simulation Adjusting the control value of Gene to create new mesh. Figure.18 Wind influence in mesh OPlab, IM, NTU

  30. 　：0m/s ：25℃ ：45% 　 ：1m/s ：25 ℃ 　 ：45% IV. Visualization tool prototype of the model 10/23 • Verification-wind Figure.19(a) Wind effect mesh Figure.19(b) Wind effect mesh Bias:17.33% Bias:16.33% OPlab, IM, NTU

  31. IV. Visualization tool prototype of the model 11/23 • Temperature( ) • experiments • Model simulation Adjusting the control value of Gene to create new mesh. Figure.20 Temperature influence in mesh OPlab, IM, NTU

  32. 　：24 ℃ ：0m/s ：55% 　 ：12 ℃ ：0m/s 　 ：55% IV. Visualization tool prototype of the model 12/23 • Verification-temperature Figure.21(a) Temperature effect mesh Figure.21(b) Temperature effect mesh Bias:0.60% Bias:1.67% OPlab, IM, NTU

  33. IV. Visualization tool prototype of the model 13/23 • Humidity( ) • experiments • Model simulation Adjusting the control value of Gene to create new mesh. Figure.22 Humidity influence in mesh OPlab, IM, NTU

  34. 　 ：70% ：0m/s ：24 ℃ ：20% ：0m/s ：24 ℃ IV. Visualization tool prototype of the model 14/23 • Verification-humidity Figure.23(b) Humidity effect mesh Figure.23(a) Humidity effect mesh Bias:0.16% Bias:0.87% OPlab, IM, NTU

  35. IV. Visualization tool prototype of the model 15/23 • Surrounding environments • To affect the area of the web • The goal of web-building is to maximize OPlab, IM, NTU

  36. Figure.24(a) Available space relatively small IV. Visualization tool prototype of the model 16/23 • Surrounding environments • experiments • Model simulation • Verification Figure.24(a) Available space relatively big OPlab, IM, NTU

  37. IV. Visualization tool prototype of the model 17/23 • Prey size • Affect mesh • Applying the past experiences for catching difference sizes of prey to adjust the mesh of the next web-building OPlab, IM, NTU

  38. IV. Visualization tool prototype of the model 18/23 • Prey size • experiments • Model simulation The major concept is that using animals learning to simulate the real world • Verification OPlab, IM, NTU

  39. Verification IV. Visualization tool prototype of the model 19/23 Figure.25(a) The first day Figure.25(b) The second day OPlab, IM, NTU

  40. Verification IV. Visualization tool prototype of the model 20/23 Figure.25(c) The third day Figure.25(d) The fourth day OPlab, IM, NTU

  41. IV. Visualization tool prototype of the model 21/23 • Summary OPlab, IM, NTU

  42. Outline • Introduction • Abstract • Motivation • Literature review • Artificial Intelligence • Related spider papers • Spider web-building algorithm design • Visualization tool prototype of the model • Internal factors • External factors • Conclusion and future work OPlab, IM, NTU

  43. V. Conclusion and future work 1/2 • Success in simulation the sequential behavior of spider web-building • The proposed model was verified by comparing with numerical experiment of biologists • Unobserved behavior of spiders could be successfully predicted OPlab, IM, NTU

  44. V. Conclusion and future work 2/2 • Long term learning • Simulating the behavior of spider to repair the web • Designing social spider web-building model • Applying spider web-building algorithms to optimization problems OPlab, IM, NTU

  45. Acknowledgements • We thank our adviser PhD Peng-Yeng Yin. • We thank NSC to provide our budget. Project name:模擬蜘蛛結網之演算法設計及視覺化工具開發 Project number:94-2815-C-260 -014 -E Adviser :尹邦嚴 Name:陳怡孜 OPlab, IM, NTU

  46. Q＆A ? OPlab, IM, NTU

  47. Thank you !! OPlab, IM, NTU

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