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Antropoidalny Model Inteligentnego Systemu Decyzyjnego dla Jednostek Autonomicznych

Abstract

Głównym celem pracy jest opracowanie modelu procesów psychologicznych -- od momentu otrzymania bodźca do momentu podjęcia adekwatnej reakcji -- zachodzących w mózgu człowieka (psychologia poznawcza), oraz teorii motywacji (potrzeb, popędów i emocji). Model, zaprezentowany w pracy nazwany Inteligentnym Systemem Decyzyjnym (ISD), może mieć zastosowanie w systemie sterowania jednostką autonomiczną (agentem). W rozprawie rozważa się budowę systemu składającego się z kilku równoległych procesów współdziałających ze sobą: poczynając od percepcji sensorycznej, poprzez spostrzeganie, uwagę, procesy pamięciowe, a kończąc na myśleniu. Procesy te zaprojektowano jako współbieżne, tak aby po pojawieniu się nowej informacji na wejściu systemu, można było szybko wygenerować reakcję. Systemy motywacyjne (potrzeby i emocje) przedstawione w pracy zostały najpełniej zweryfikowane w symulacji autonomicznego kierowcy.

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Category:
Thesis, nostrification
Type:
praca doktorska pracowników zatrudnionych w PG oraz studentów studium doktoranckiego
Language:
Polish
Publication year:
2017
Bibliography: test
  1. na dogodne wyjaśnienie zagadnień związanych z reprezentacją wiedzy, a co za tym idzie - ze sposobem przetwarzania danych sensorycznych. Oryginalny naukowy wkład rozprawy można podsumować w następujących punktach: • przegląd i analiza zagadnień z zakresu psychologii poznawczej i teorii motywacji • porównanie aktualnie dostępnych robotów humanoidalnych (Kowalczuk i Czubenko, 2015) • przegląd rozwiązań z zakresu modelowania emocji (Kowalczuk i Czubenko, 2016) • analiza architektur kognitywnych (Kowalczuk i Czubenko, 2017a) • opracowanie odpowiednich modeli psychologii (Kowalczuk i Czubenko, 2010b, 2011a) • opracowanie algorytmów podejmowania decyzji agenta na podstawie potrzeb (Ko- walczuk i Czubenko, 2010a, 2011b; Kowalczuk et al., 2016) • zaprojektowanie mechanizmu ewolucji emocji związanej z postrzeganymi obiektami (Kowalczuk i Czubenko, 2013a, 2017b) • szczegółowe opracowanie mechanizmów uwagi agenta • implementacja systemu ISD w środowisku mikrorobotyckim (Kowalczuk i Czubenko, 2011b) • implementacja systemu xDriver w środowisku symulacyjnym (Czubenko et al., 2015). open in new tab
  2. Udowodnione powyżej tezy pomocnicze pracy składają się w całość i pozwalają na stwierdzenie, że w ogólności model procesów psychologicznych człowieka może być pod- stawą budowy inteligentnego systemu decyzyjnego jednostek autonomicznych, co było głównym zamierzeniem niniejszej rozprawy. Spis rysunków open in new tab
  3. Cztery temperamenty wg Galena. . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2 Model procesów poznawczych. . . . . . . . . . . . . . . . . . . . . . . . . . . 11
  4. Spostrzeżenie jako wynik odbioru informacji sensorycznych. . . . . . . . . . 12
  5. Schematyczny diagram reprezentacji podwójnego kodowania. . . . . . . . . 13
  6. Droga selekcji informacji. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
  7. Teoria uwagi Broadbenta. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
  8. Wielokrotny filtr uwagi Treisman. . . . . . . . . . . . . . . . . . . . . . . . . 18
  9. Teoria łączonego filtru. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
  10. Teoria alokacji zasobów Kahnemana. . . . . . . . . . . . . . . . . . . . . . . 21 2.10 Teoria alokacji zasobów Navona. . . . . . . . . . . . . . . . . . . . . . . . . 22
  11. Graficzna reprezentacja świadomości. . . . . . . . . . . . . . . . . . . . . . . 23
  12. Model pamięci wg Atkinsona. . . . . . . . . . . . . . . . . . . . . . . . . . . 24
  13. Model pamięci roboczej Baddeleya. . . . . . . . . . . . . . . . . . . . . . . . 26
  14. Mural reprezentujący wiedzę na Bibliotece Kongresu. . . . . . . . . . . . . . 28
  15. Przykład sieci semantycznej. . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
  16. Rodzaje pamięci długotrwałej. . . . . . . . . . . . . . . . . . . . . . . . . . 30
  17. Model pamięci Lehrla i Fishera. . . . . . . . . . . . . . . . . . . . . . . . . . 31
  18. Fazy procesów pamięciowych. . . . . . . . . . . . . . . . . . . . . . . . . . . 33 open in new tab
  19. Krzywe zapominania Ebbinghausa. . . . . . . . . . . . . . . . . . . . . . . . 36
  20. Uproszczona piramida potrzeb Maslowa. . . . . . . . . . . . . . . . . . . . . 43
  21. Procesy aktywacji emocji. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
  22. Diagram wielowymiarowej emocji Russella i Thayera. . . . . . . . . . . . . . 48 open in new tab
  23. Model emocji Posenra. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
  24. Kostka Lövheima. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
  25. Rozpięta parabolida emocji Plutchika. . . . . . . . . . . . . . . . . . . . . . 50
  26. Podział zjawisk emocjonalnych. . . . . . . . . . . . . . . . . . . . . . . . . . 52 open in new tab
  27. Zjawisko powszechnie zwane jako Uncanny Valley; prawa autorskie: Smur- rayinchester, Wikipedia Commons, GDFL. . . . . . . . . . . . . . . . . . . . 56
  28. Przegląd robotów humanoidalnych. . . . . . . . . . . . . . . . . . . . . . . . 58
  29. Roboty NAO, Aldebaran Robotics; prawa autorskie: J. Kemtchuaing, Al- debaran. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
  30. Robot FLASH; prawa autorskie: Jan Kędzierski, Politechnika Wrocławska. . 62
  31. Model intelektu Guilforda. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
  32. Architektura poznawcza LIDA. . . . . . . . . . . . . . . . . . . . . . . . . . 77
  33. Architektura kognitywna CLARION. . . . . . . . . . . . . . . . . . . . . . . 78 open in new tab
  34. System poznawczy Soar w wersji 9. . . . . . . . . . . . . . . . . . . . . . . . 79 open in new tab
  35. Wystawa samochodów przyszłości z 1939 roku w Nowym Yorku. . . . . . . 81 open in new tab
  36. Klasyfikacja niebezpiecznych aktów drogowych. . . . . . . . . . . . . . . . . 83
  37. Percepcja w ISD. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 open in new tab
  38. Wykrywanie krawędzi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
  39. Transformaty Hugh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 open in new tab
  40. Wykrywanie narożników. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
  41. Wykrywanie kleksów. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
  42. Kaskada Haara wykrywająca twarz. . . . . . . . . . . . . . . . . . . . . . . 95 open in new tab
  43. Cechy charakterystyczne obrazu. . . . . . . . . . . . . . . . . . . . . . . . . 96
  44. Skan dźwiękowy kanionu w morzu Czerwonym. . . . . . . . . . . . . . . . . 98
  45. Przykład prostego wrażenia. . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 4.10 Przykład wrażenia 'barwa'. . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
  46. Triangulacja i rozmiary figury płaskiej. . . . . . . . . . . . . . . . . . . . . . 103
  47. Domyślne zbiory rozmyte. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
  48. Rozmyte funkcje przynależności barw. . . . . . . . . . . . . . . . . . . . . . 105
  49. Stopień uogólnienia elementów poznawczych ISD. . . . . . . . . . . . . . . . 106
  50. Złożone wrażenie 'koloru osobnika'. . . . . . . . . . . . . . . . . . . . . . . . 108 open in new tab
  51. Podobieństwo wrażeń rozmytych. . . . . . . . . . . . . . . . . . . . . . . . . 112
  52. Struktura spostrzeżeń. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
  53. Przykładowe drzewo semantyczne. . . . . . . . . . . . . . . . . . . . . . . . 115
  54. Ścieżka informacji w ISD. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
  55. Model pamięci agenta, przepływy oraz typy danych w systemie ISD. . . . . 123 open in new tab
  56. Przykładowa zawartość pamięci sceny (widziana przez człowieka). . . . . . . 126
  57. Przykładowy wycinek pamięci sceny z obwiedniami obiektów. . . . . . . . . 127
  58. Model pamięci długotrwałej. . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
  59. Szczegółowy podział pamięci semantycznej. . . . . . . . . . . . . . . . . . . 129
  60. Uproszczony, schematyczny model abstrakcyjnej pamięci semantycznej. . . . 130 open in new tab
  61. Wizualizacja przestrzenna pamięci semantycznej. . . . . . . . . . . . . . . . 131
  62. Model rozmyty potrzeby agenta w systemie ISD. . . . . . . . . . . . . . . . 139
  63. Funkcja skalująca funkcję wagi potrzeby. . . . . . . . . . . . . . . . . . . . . 140
  64. Robotycki odpowiednik piramidy Maslowa. . . . . . . . . . . . . . . . . . . 141
  65. Komponenty emocjonalne systemu ISD i relacje między nimi. . . . . . . . . 142
  66. Koło (części rzeczywistej) emocji systemu xEmotion. . . . . . . . . . . . . . 144
  67. Przekrój przez koło emocji. . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
  68. Graficzna ilustracja kwaternionów w Q. . . . . . . . . . . . . . . . . . . . . 146 open in new tab
  69. Liniowy model emocji. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
  70. Funkcja przejścia od emocji liniowej do nastroju. . . . . . . . . . . . . . . . 147
  71. Sposób generowania stanów emocji (klasycznej i nastroju). . . . . . . . . . . 149
  72. Ewolucja klasycznej emocji. . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
  73. Trzeci 'wymiar' emocji klasycznej. . . . . . . . . . . . . . . . . . . . . . . . 151
  74. Przykładowa potrzeba przy po długotrwałym wpływie nastroju. . . . . . . . 153
  75. Proces tworzenia komponentów emocjonalnych agenta. . . . . . . . . . . . . 154
  76. Uproszczony schemat mechanizmów myślenia. . . . . . . . . . . . . . . . . . 156
  77. Wyznaczanie celów agenta. . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 open in new tab
  78. Rozszerzenie koncepcji potrzeby o nowy wymiar. . . . . . . . . . . . . . . . 157
  79. Prezentacja norm [⋆ T ] i [⋆ S ] Einsteina. . . . . . . . . . . . . . . . . . . . 158 open in new tab
  80. Rozmyto-neuronowa sieć oceniająca zastosowanie reakcji. . . . . . . . . . . 161
  81. Prezentacja rozmytej implikacji Łukasiewicza. . . . . . . . . . . . . . . . . . 169 open in new tab
  82. Prezentacja norm [ * T ] i [ * S ] Łukasiewicza. . . . . . . . . . . . . . . . . . 170 open in new tab
  83. Przykładowe zastosowanie MPP. . . . . . . . . . . . . . . . . . . . . . . . . 171
  84. Robot qFix firmy KTB mechatronics . . . . . . . . . . . . . . . . . . . . . . 176
  85. Algorytm wyboru kolejnej reakcji w ISD. . . . . . . . . . . . . . . . . . . . 180
  86. Część pamięci semantycznej agenta xDriver. . . . . . . . . . . . . . . . . . . 182
  87. Prędkość pojazdu sterowanego przez xDrivera. . . . . . . . . . . . . . . . . 186 5.5 Ostre wartości potrzeb xDrivera. . . . . . . . . . . . . . . . . . . . . . . . . 186
  88. Prędkość samochodu sterowanego przez kontroler PI. . . . . . . . . . . . . . 188 5.7 Prędkość xDrivera podczas symulacji. . . . . . . . . . . . . . . . . . . . . . 190 5.8 Ewolucja emocji xDrivera. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 5.9 Ewolucja składowych emocjonalnych w czasie. . . . . . . . . . . . . . . . . . 191 5.10 Szczegóły (przybliżenie) ewolucji zmiennych emocjonalnych. . . . . . . . . . 192 5.11 Okno ekspozycji obiektów skojarzonych z emocjami. . . . . . . . . . . . . . 193
  89. Spis tablic open in new tab
  90. Gra jednoosobowa przedstawiająca problem czujności. . . . . . . . . . . . . 20
  91. Zestawienie emocji podstawowych. . . . . . . . . . . . . . . . . . . . . . . . 51
  92. Zestawienie cech robotów humanoidalnych. . . . . . . . . . . . . . . . . . . 57
  93. Emocja, a zmienne ocennye w teorii OCC. . . . . . . . . . . . . . . . . . . . 68
  94. Porównanie systemów obliczeniowych emocji. . . . . . . . . . . . . . . . . . 72
  95. Porównanie architektur kognitywnych. . . . . . . . . . . . . . . . . . . . . . 80
  96. Tworzenie złożonego wrażenia. . . . . . . . . . . . . . . . . . . . . . . . . . 107
  97. Relacje pierwotne i operacje na spostrzeżeniach. . . . . . . . . . . . . . . . . 117
  98. Sposób wyliczania nastroju. . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
  99. Mapowanie elementarnych elementów ISD do DL. . . . . . . . . . . . . . . 165
  100. Mapowanie złożonych elementów ISD do DL. . . . . . . . . . . . . . . . . . 166
  101. Reakcje agenta. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 open in new tab
  102. Esytmacja stanu agenta. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 open in new tab
  103. Efekt działania FNN. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
  104. Symulacja xDriver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
  105. Lista reguł wpływu środowiska na system potrzeb agenta. . . . . . . . . . . 185
  106. Reakcje i emocje agenta. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 open in new tab
  107. Scenariusz obiektów z kontekstem emocjonalnym. . . . . . . . . . . . . . . . 192
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