1. Analogy-Making

2. Consider the following cognitive activities

3. Recognition:

4. –A child learns to recognize cats and dogs in books as well as in real life.

5. Recognition: –A child learns to recognize cats and dogs in books as well as in real life.

6. –People can recognize letters of the alphabet, e.g., ‘A’, in many different typefaces and handwriting styles.

8. –People can recognize styles of music:

9. “That sounds like Mozart”

10. –People can recognize styles of music: “That sounds like Mozart” “That’s a muzak version of ‘Hey Jude’”

11. –People can recognize styles of music: “That sounds like Mozart” “That’s a muzak version of ‘Hey Jude’” –People can recognize abstract situations:

12. –People can recognize styles of music: “That sounds like Mozart” “That’s a muzak version of ‘Hey Jude’” –People can recognize abstract situations: A “Cinderella story” “Another Vietnam” “Monica-gate” “Shop-aholic”

13. People make scientific analogies:

14. –“Biological competition is like economic competition” (Darwin)

15. People make scientific analogies: –“Biological competition is like economic competition” (Darwin) –“The nuclear force is like the electromagnetic force” (Yukawa)

16. People make scientific analogies: –“Biological competition is like economic competition” (Darwin) –“The nuclear force is like the electromagnetic force” (Yukawa) –“The computer is like the brain” (von Neumann)

17. People make scientific analogies: –“Biological competition is like economic competition” (Darwin) –“The nuclear force is like the electromagnetic force” (Yukawa) –“The computer is like the brain” (von Neumann) –“The brain is like the computer” (Simon, Newell, etc.)

18. People make unconscious analogies

19. Man: “I’m going shopping for a valentine for my wife.”

20. People make unconscious analogies Man: “I’m going shopping for a valentine for my wife.” Female colleague: “I did that yesterday.”

21. People make unconscious analogies Newly married woman: “I often forget my new last name”

22. People make unconscious analogies Newly married woman: “I often forget my new last name” Man: “I have that trouble every January”

23. People make unconscious analogies Computer scientist: “I’m in artificial intelligence because it’s a mixture of psychology, philosophy, linguistics, and computer science”

24. People make unconscious analogies Computer scientist: “I’m in artificial intelligence because it’s a mixture of psychology, philosophy, linguistics, and computer science” Architect: “That’s the reason I’m in architecture”

25. What is common to all these examples?

26. Copycat (Douglas Hofstadter, Melanie Mitchell, Jim Marshall)

27. Idealizing analogy-making abc ---> abd ijk --->

28. Idealizing analogy-making abc ---> abd ijk ---> ijl (replace rightmost letter by successor)

29. Idealizing analogy-making abc ---> abd ijk ---> ijl (replace rightmost letter by successor) ijd (replace rightmost letter by ‘d’)

30. Idealizing analogy-making abc ---> abd ijk ---> ijl (replace rightmost letter by successor) ijd (replace rightmost letter by ‘d’) ijk (replace all ‘c’ s by ‘d’ s )

31. Idealizing analogy-making abc ---> abd ijk ---> ijl (replace rightmost letter by successor) ijd (replace rightmost letter by ‘d’) ijk (replace all ‘c’ s by ‘d’ s ) abd (replace any string by ‘abd’)

32. Idealizing analogy-making abc ---> abd iijjkk ---> ?

33. Idealizing analogy-making abc ---> abd iijjkk ---> iijjkl Replace rightmost letter by successor

34. Idealizing analogy-making abc ---> abd iijjkk ---> ?

35. Idealizing analogy-making abc ---> abd iijjkk ---> iijjll Replace rightmost “letter” by successor

36. Idealizing analogy-making abc ---> abd kji ---> ?

37. Idealizing analogy-making abc ---> abd kji ---> kjj Replace rightmost letter by successor

38. Idealizing analogy-making abc ---> abd kji ---> ?

39. Idealizing analogy-making abc ---> abd kji ---> lji Replace “rightmost” letter by successor

40. Idealizing analogy-making abc ---> abd kji ---> ?

41. Idealizing analogy-making abc ---> abd kji ---> ?

42. Idealizing analogy-making abc ---> abd kji ---> kjh Replace rightmost letter by “successor”

43. Idealizing analogy-making abc ---> abd mrrjjj ---> ?

44. Idealizing analogy-making abc ---> abd mrrjjj ---> mrrjjk Replace rightmost letter by successor

45. Idealizing analogy-making abc ---> abd mrrjjj ---> ?

46. Idealizing analogy-making abc ---> abd mrrjjj ---> ? 1 2 3

47. Idealizing analogy-making abc ---> abd mrrjjj ---> ? 1 2 3 1 2 4

48. Idealizing analogy-making abc ---> abd mrrjjj ---> mrrjjjj 1 2 3 Replace rightmost “letter” by successor 1 2 4

49. Idealizing analogy-making abc ---> abd xyz ---> ?

50. Idealizing analogy-making abc ---> abd xyz ---> xya Replace rightmost letter by successor

51. Idealizing analogy-making abc ---> abd xyz ---> xya (not allowed) Replace rightmost letter by successor

52. Idealizing analogy-making abc ---> abd xyz ---> ?

53. Idealizing analogy-making abc ---> abd xyz ---> ? last letter in alphabet

54. Idealizing analogy-making abc ---> abd xyz ---> ? last letter in alphabet first letter in alphabet

55. Idealizing analogy-making abc ---> abd xyz ---> ? last letter in alphabet first letter in alphabet

56. Idealizing analogy-making abc ---> abd xyz ---> wyz last letter in alphabet first letter in alphabet Replace “rightmost” letter by “successor”

57. Idealizing analogy-making abc ---> abd xyz ---> wyz last letter in alphabet first letter in alphabet

58. Abilities needed in the letter-string microworld

59. The Copycat program (Hofstadter and Mitchell)

60. Inspired by collective behavior in complex systems (e.g., ant colonies)

61. The Copycat program (Hofstadter and Mitchell) Inspired by collective behavior in complex systems (e.g., ant colonies) Understanding and perception of similarity is built up collectively by many independent simple “agents” working in parallel

62. The Copycat program (Hofstadter and Mitchell) Inspired by collective behavior in complex systems (e.g., ant colonies) Understanding and perception of similarity is built up collectively by many independent simple “agents” working in parallel Each agent has very limited perceptual and communication abilities

63. The Copycat program (Hofstadter and Mitchell) Inspired by collective behavior in complex systems (e.g., ant colonies) Understanding and perception of similarity is built up collectively by many independent simple “agents” working in parallel Each agent has very limited perceptual and communication abilities Teams of agents explore different possibilities for structures, building on what previous teams have constructed.

64. The Copycat program (Hofstadter and Mitchell) Inspired by collective behavior in complex systems (e.g., ant colonies) Understanding and perception of similarity is built up collectively by many independent simple “agents” working in parallel Each agent has very limited perceptual and communication abilities Teams of agents explore different possibilities for structures, building on what previous teams have constructed. The resources (agent time) allocated to a possible structure depends on its promise, as assessed dynamically as exploration proceeds.

65. The Copycat program (Hofstadter and Mitchell) Inspired by collective behavior in complex systems (e.g., ant colonies) Understanding and perception of similarity is built up collectively by many independent simple “agents” working in parallel Each agent has very limited perceptual and communication abilities Teams of agents explore different possibilities for structures, building on what previous teams have constructed. The resources (agent time) allocated to a possible structure depends on its promise, as assessed dynamically as exploration proceeds. The agents working together produce an “emergent” understanding of the analogy.

66. Architecture of Copycat

67. Concept network (Slipnet) Architecture of Copycat

68. Concept network (Slipnet) a b c ---> a b d i i j j k k --> ? Architecture of Copycat Workspace

69. Concept network (Slipnet) a b c ---> a b d i i j j k k --> ? Perceptual and structure-building agents (codelets) Architecture of Copycat Workspace

70. Concept network (Slipnet) a b c ---> a b d i i j j k k --> ? Perceptual and structure-building agents (codelets) Architecture of Copycat Temperature Workspace

72. The Workspace starts out with letters in the analogy problem and their initial descriptions. Workspace

73. a b c --> a b d m r r j j j --> ?

74. a b c --> a b d m r r j j j --> ? A leftmost letter B middle letter C rightmost letter A leftmost letter B middle letter D rightmost letter M leftmost letter J leftmost letter R letter R letter J letter J letter

75. The Workspace starts out with letters in the analogy problem and their initial descriptions. Codelets gradually build up additional descriptions and structures. Workspace

76. a b c --> a b d m r r j j j --> ?

77. a b c --> a b d m r r j j j --> ?

78. Codelets can be either “bottom-up” (noticers) or “top- down” (seekers). Workspace

79. a b c --> a b d m r r j j j --> ?

80. a b c --> a b d m r r j j j --> ? successorship

81. a b c --> a b d m r r j j j --> ? successorship

82. Codelets make probabilistic decisions: Workspace

83. Codelets make probabilistic decisions: –What to look at next Workspace

84. Codelets make probabilistic decisions: –What to look at next –Whether to build a structure there Workspace

85. Codelets make probabilistic decisions: –What to look at next –Whether to build a structure there –How fast to build it Workspace

86. Codelets make probabilistic decisions: –What to look at next –Whether to build a structure there –How fast to build it –Whether to destroy an existing structure there Workspace

87. a b c --> a b d m r r j j j --> ?

88. a b c --> a b d m r r j j j --> ? rightmost --> rightmost?? letter --> letter??

89. a b c --> a b d m r r j j j --> ? rightmost --> rightmost? letter --> letter?

90. a b c --> a b d m r r j j j --> ? rightmost --> rightmost? letter --> letter? leftmost --> leftmost?? letter --> letter??

91. a b c --> a b d m r r j j j --> ? rightmost --> rightmost letter --> letter leftmost --> leftmost?? letter --> letter??

92. a b c --> a b d m r r j j j --> ? rightmost --> rightmost letter --> letter leftmost --> leftmost?? letter --> letter??

93. a b c --> a b d m r r j j j --> ? rightmost --> rightmost letter --> letter leftmost --> leftmost?? letter --> letter?? rightmost --> rightmost?? letter --> group??

94. a b c --> a b d m r r j j j --> ? rightmost --> rightmost letter --> letter leftmost --> leftmost?? letter --> letter?? rightmost --> rightmost? letter --> group?

95. a b c --> a b d m r r j j j --> ? leftmost --> leftmost? letter --> letter? rightmost --> rightmost letter --> group

96. a b c --> a b d m r r j j j --> ? leftmost --> leftmost? letter --> letter? rightmost --> rightmost letter --> group leftmost --> rightmost?? letter --> letter??

97. a b c --> a b d m r r j j j --> ? leftmost --> leftmost? letter --> letter? rightmost --> rightmost letter --> group high prob. low prob. leftmost --> rightmost?? letter --> letter??

98. Probabilities are used to insure that no possibilities are ruled out in principle, but that not all possibilities have to be considered.

99. These decisions rely on information being obtained as the run takes place, e.g., pressure from current activation of concepts and neighboring structures.

100. Probabilities are used to insure that no possibilities are ruled out in principle, but that not all possibilities have to be considered. These decisions rely on information being obtained as the run takes place, e.g., pressure from current activation of concepts and neighboring structures. Therefore, the probabilities have to be updated continually.

101. Slipnet

102. Part of Copycat’s Slipnet

103. Slipnet Concepts are activated as instances are noticed in workspace.

104. a b c --> a b d x y z --> ?

105. a b c --> a b d x y z --> ?

106. Part of Copycat’s Slipnet successor

107. Slipnet Activation of concepts feeds back into “top-down” pressure to notice instances of those concepts in the workspace.

108. a b c --> a b d x y z --> ? successor

109. a b c --> a b d x y z --> ? successor

110. a b c --> a b d x y z --> ? successor

111. Slipnet Activated concepts spread activation to neighboring concepts.

112. a b c --> a b d x y z --> ? last

113. a b c --> a b d x y z --> ? last first

114. a b c --> a b d x y z --> ? last first

115. Slipnet Activation of link concepts determines current ease of slippages of that type (e.g., “opposite”).

116. a b c --> a b d x y z --> ? first last leftmost rightmost

117. a b c --> a b d x y z --> ? first last leftmost rightmost

118. a b c --> a b d x y z --> ? first last opposite first last first --> last leftmost rightmost

119. a b c --> a b d x y z --> ? first last opposite first last leftmostrightmost first --> last leftmost rightmost

120. a b c --> a b d x y z --> ? first last opposite first last leftmostrightmost first --> last leftmost rightmost

121. a b c --> a b d x y z --> ? first last opposite first last leftmostrightmost first --> last rightmost --> leftmost leftmost rightmost

122. Temperature

123. Measures how well organized the program’s “understanding” is as processing proceeds (a reflection of how good the current worldview is) Temperature

124. Measures how well organized the program’s “understanding” is as processing proceeds (a reflection of how good the current worldview is) –Little organization —> high temperature Temperature

125. Measures how well organized the program’s “understanding” is as processing proceeds (a reflection of how good the current worldview is) –Little organization —> high temperature –Lots of organization —> low temperature Temperature

126. a b c --> a b d m r r j j j --> ? High temperature leftmost --> leftmost? letter --> letter? rightmost --> rightmost?? letter --> group??

127. a b c --> a b d m r r j j j --> ? Medium temperature leftmost --> leftmost? letter --> letter? rightmost --> rightmost letter --> group

128. a b c --> a b d m r r j j j --> ? leftmost --> leftmost letter --> group rightmost --> rightmost letter --> group Low temperature middle --> middle letter --> group

129. Measures how well organized the program’s “understanding” is as processing proceeds (a reflection of how good the current worldview is) –Little organization —> high temperature –Lots of organization —> low temperature Temperature

130. Measures how well organized the program’s “understanding” is as processing proceeds (a reflection of how good the current worldview is) –Little organization —> high temperature –Lots of organization —> low temperature Temperature feeds back to codelets: Temperature

131. Measures how well organized the program’s “understanding” is as processing proceeds (a reflection of how good the current worldview is) –Little organization —> high temperature –Lots of organization —> low temperature Temperature feeds back to codelets: –High temperature —> low confidence in decisions —> decisions are made more randomly Temperature

132. Measures how well organized the program’s “understanding” is as processing proceeds (a reflection of how good the current worldview is) –Little organization —> high temperature –Lots of organization —> low temperature Temperature feeds back to codelets: –High temperature —> low confidence in decisions —> decisions are made more randomly –Low temperature —> high confidence in decisions —> decisions are made more deterministically Temperature

133. Measures how well organized the program’s “understanding” is as processing proceeds (a reflection of how good the current worldview is) –Little organization —> high temperature –Lots of organization —> low temperature Temperature feeds back to codelets: –High temperature —> low confidence in decisions —> decisions are made more randomly –Low temperature —> high confidence in decisions —> decisions are made more deterministically Result: System gradually goes from random, parallel, bottom-up processing to deterministic, serial, top-down processing Temperature

134. Demo

135. What’s needed to apply these ideas in “real world” problems?

136. Much expanded repertoire of concepts

137. What’s needed to apply these ideas in “real world” problems? Much expanded repertoire of concepts Ability to generate temporary concepts on the fly

138. What’s needed to apply these ideas in “real world” problems? Much expanded repertoire of concepts Ability to generate temporary concepts on the fly (e.g., abc ---> abd, ace ---> ?)

139. What’s needed to apply these ideas in “real world” problems? Much expanded repertoire of concepts Ability to generate temporary concepts on the fly (e.g., abc ---> abd, ace ---> ?) Ability to learn new permanent concepts

140. What’s needed to apply these ideas in “real world” problems? Much expanded repertoire of concepts Ability to generate temporary concepts on the fly (e.g., abc ---> abd, ace ---> ?) Ability to learn new permanent concepts (e.g., bbb ---> ddd, ppp ---> ?)

141. What’s needed to apply these ideas in “real world” problems? Much expanded repertoire of concepts Ability to generate temporary concepts on the fly (e.g., abc ---> abd, ace ---> ?) Ability to learn new permanent concepts (e.g., bbb ---> ddd, ppp ---> ?) Ability for “self-watching”

142. What’s needed to apply these ideas in “real world” problems? Much expanded repertoire of concepts Ability to generate temporary concepts on the fly (e.g., abc ---> abd, ace ---> ?) Ability to learn new permanent concepts (e.g., bbb ---> ddd, ppp ---> ?) Ability for “self-watching” (e.g., abc ---> abd, xyz ---> ?)

143. What’s needed to apply these ideas in “real world” problems? Much expanded repertoire of concepts Ability to generate temporary concepts on the fly (e.g., abc ---> abd, ace ---> ?) Ability to learn new permanent concepts (e.g., bbb ---> ddd, ppp ---> ?) Ability for “self-watching” (e.g., abc ---> abd, xyz ---> ?) (cf. Marshall, Metacat, Ph.D. Dissertation, Indiana University, 1998)

144. Applications of Ideas from Copycat

145. Letter recognition (McGraw, 1995, Ph.D Dissertation, Indiana University)

146. Applications of Ideas from Copycat Letter recognition (McGraw, 1995, Ph.D Dissertation, Indiana University) Natural language processing (Gan, Palmer, and Lua, Computational Linguistics 22(4), 1996, pp. 531-553)

147. Applications of Ideas from Copycat Letter recognition (McGraw, 1995, Ph.D Dissertation, Indiana University) Natural language processing (Gan, Palmer, and Lua, Computational Linguistics 22(4), 1996, pp. 531-553) Robot control (Lewis and Lugar, Proceedings of the 22nd Annual Conference of the Cognitive Science Society, Erlbaum, 2000.)

148. Applications of Ideas from Copycat Letter recognition (McGraw, 1995, Ph.D Dissertation, Indiana University) Natural language processing (Gan, Palmer, and Lua, Computational Linguistics 22(4), 1996, pp. 531-553) Robot control (Lewis and Lugar, Proceedings of the 22nd Annual Conference of the Cognitive Science Society, Erlbaum, 2000.) Image understanding (Mitchell et al.)