Unifying conceptual spaces: Concept formation in musical creative systems

Minds and Machines

Volumn 20, Issue 4, 2010, Pages 503-532

  Forth, Jamie ^a   Wiggins, Geraint A ^a   McLean, Alex ^a  

^a UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

Conceptual spaces; Creativity; Geometry; Musical rhythm; Search; Similarity

Indexed keywords

CONCEPTUAL SPACES; CREATIVITY; MUSICAL RHYTHM; SEARCH; SIMILARITY;

COMPUTATIONAL GEOMETRY; GALLIUM;

KNOWLEDGE REPRESENTATION;

EID: 78650746035     PISSN: 09246495     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11023-010-9207-x     Document Type: Article

References (58)

1. J. Aisbett G. Gibbon 2001 A general formulation of conceptual spaces as a meso level representation Artificial Intelligence 133 1-2 189 232 0992.68195 10.1016/S0004-3702(01)00144-8 1867502 (Pubitemid 33076558)
2. Baars, B. J. (1988). A cognitive theory of consciousness. Cambridge: Cambridge University Press.
3. W. E. Benjamin 1984 A theory of musical meter Music Perception 1 4 355 413
4. M. A. Boden 1998 Creativity and artificial intelligence Artificial Intelligence Journal 103 347 356 0910.68161 10.1016/S0004-3702(98)00055-1 1652673
5. Boden, M. A. (2004). The creative mind: Myths and mechanisms, (2nd ed.). London, UK: Routledge.
6. Bown, O., & Wiggins, G. A. (2009). From maladaptation to competition to cooperation in the evolution of musical behaviour. Musicæ Scientiæ (special issue on evolution of music).
7. Brachman, R. J., & Levesque, H. J., (Eds.). (1985). Readings in knowledge representation. Los Altos: Morgan Kaufmann.
8. A. Caclin E. Brattico M. Tervaniemi R. Näätänen D. Morlet M.-H. Giard S. McAdams 2006 Separate neural processing of timbre dimensions in auditory sensory memory Journal Cognitive Neuroscience 18 12 1959 1972 10.1162/jocn.2006.18.12.1959 (Pubitemid 44913353)
9. F. Carota A. Posada S. Harquel C. Delpuech O. Bertrand A. Sirigu 2009 Neural dynamics of the intention to speak Cerebral Cortex 20 8 1891 1897 10.1093/cercor/bhp255
10. Chew, E. (2000). Towards a mathematical model of tonality. PhD thesis, Department of Operations Research. Massachusetts: MIT, Cambridge.
11. Clarke, E. F. (1999). Rhythm and timing in music. In D. Deutsch (Eds.), Psychology of music (2nd ed. pp. 473-500). San Diego, CA: University of California.
12. Cooper, G. W., & Meyer, L. B. (1960). The rhythmic structure of music. Chicago, IL: University of Chicago Press.
13. W. J. Dowling 1978 Scale and contour: Two components of a theory of memory for melodies Psychological Review 85 4 341 354 10.1037/0033-295X.85.4.341
14. Fraisse, P. (1978). Time and rhythm perception. In E. Carterette, & M. Friedmans (Eds.), Handbook of perception (Vol. 2, pp. 203-254). New York, NY: Academic Press
15. Gabrielsson, A. (1993). The complexities of rhythm. In T. J. Tighe, & W. J. Dowling (Eds.), Psychology and music: The understanding of melody and rhythm (pp. 93-120). Hillside, NJ: Lawrence Erlbaum Associates, Inc.
16. Gärdenfors, P. (2000). Conceptual spaces: The geometry of thought. Cambridge, MA: MIT Press.
17. Gärdenfors, P. (2007). Representing actions and functional properties in conceptual spaces. In T. Ziemke, J. Zlatev, & R. M. Frank (Eds.), Body, language and mind (Vol. 1, pp. 167-195). Berlin, Germany: Mouton de Gruyter.
18. Guilford, J. (1967). The nature of human intelligence. New York: McGraw-Hill.
19. K. Haase 1995 Too many ideas, just one word: a review of Margaret Boden's The creative mind: Myths and mechanisms Artificial Intelligence Journal 79 69 82 10.1016/0004-3702(95)90024-1
20. Hasty, C. F. (1997). Metre as rhythm. Oxford: Oxford University Press.
21. A. Jain K. Nandakumar A. Ross 2005 Score normalization in multimodal biometric systems Pattern Recognition 38 12 2270 2285 10.1016/j.patcog.2005.01. 012 (Pubitemid 41336698)
22. Koestler, A. (1964). The act of creation. London: Hutchinson & Co.
23. Lemström, K., & Wiggins, G. A. (2009). Formalizing invariances for content-based music retrieval. In G. Tzanetakis & K. Hirata (Eds.), Proceedings of ISMIR 2009.
24. Lerdahl, F., & Jackendoff, R. (1983). A generative theory of tonal music. Cambridge, MA: MIT Press.
25. London, J. (2004). Hearing in time: Psychological aspects of music metre. Oxford, UK: Oxford University Press.
26. R. Lustig 1995 Margaret Boden, the creative mind: Myths and mechanisms Artificial Intelligence Journal 79 83 96 10.1016/0004-3702(95)90025-X
27. MacKay, D. J. C. (1998). Introduction to Monte Carlo methods. In M. I. Jordan (Ed.), Learning in graphical models, NATO science series (pp. 175-204). Dordrecht, The Netherlands: Kluwer.
28. Müllensiefen, D. (2009). Fantastic: Feature analysis technology accessing statistics (in a corpus). Technical report, Goldsmiths, London, UK: University of London.
29. R. Parncutt 1994 A perceptual model of pulse salience and metrical accent in musical rhythms Music Perception 11 409 464
30. Parsons, D. (1975). The directory of tunes and musical themes. Cambridge, UK: S. Brown.
31. Patel, A. D. (2008). Music, language, and the brain. Oxford: Oxford University Press.
32. M. T. Pearce G. A. Wiggins 2006 Expectation in melody: The influence of context and learning Music Perception 23 5 377 405 10.1525/mp.2006.23.5.377
33. D. Perkins 1995 An unfair review of Margaret Boden's the creative mind from the perspective of creative systems Artificial Intelligence Journal 79 97 109 10.1016/0004-3702(95)90026-8
34. D.-J. Povel 1984 A theoretical framework for rhythm perception Psychological Research 45 4 315 337 10.1007/BF00309709
35. R Development Core Team. (2010). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. ISBN 3-900051-07-0.
36. A. Ram L. Wills E. Domeshek N. Nersessian J. Kolodner 1995 Understanding the creative mind: a review of Margaret Boden's creative mind Artificial Intelligence Journal 79 111 128 10.1016/0004-3702(95)90027-6
37. Raubal, M. (2004). Formalizing conceptual spaces. In A. Varzi & L. Vieu (Eds.), Formal ontology in information systems, proceedings of the third international conference (FOIS 2004), Vol. 114 of frontiers in artificial intelligence and applications (pp. 153-164). Amsterdam, NL: IOS Press.
38. Raubal, M. (2008a). Cognitive modeling with conceptual spaces. In M. Ragni, H. Schultheis, & T. Barkowsky (Eds.), Workshop on cognitive models of human spatial reasoning (pp. 7-11). Freiburg, Germany.
39. Raubal, M. (2008b). Representing concepts in time. In C. Freksa, N. S. Newcombe, Peter Gärdenfors, & S. Wölfl (Eds.), Spatial cognition VI. Learning, reasoning, & talking about space. Lecture Notes in Computer Science (Vol. 5248, pp. 328-343). Berlin: Springer.
40. J. T. Rickard 2006 A concept geometry for conceptual spaces Fuzzy Optimization and Decision Making 5 4 311 329 1127.68103 10.1007/s10700-006-0020- 1 2265886 (Pubitemid 44450821)
41. Rickard, J. T., Aisbett, J., & Gibbon, G. (2007a). Knowledge representation and reasoning in conceptual spaces. In Foundations of Computational Intelligence, 2007. FOCI 2007. IEEE Symposium on (pp. 583-590).
42. J. T. Rickard J. Aisbett G. Gibbon 2007 Reformulation of the theory of conceptual spaces Information Sciences 177 21 4539 4565 1126.68078 10.1016/j.ins.2007.05.023 2351233 (Pubitemid 47238796)
43. Roberson, D., Davidoff, J., Davies, I. R. L., & Shapiro, L. R. (2006). Colour categories and category acquisition in Himba and English. In N. Pitchford & C. Bingham (Eds.), Progress in colour studies (pp. 159-172). Amsterdam: John Benjamins.
44. R. Schank D. Foster 1995 The engineering of creativity: A review of Boden's the creative mind Artificial Intelligence Journal 79 129 143 10.1016/0004-3702(95)90028-4
45. Schwering, A., & Raubal, M. (2005a). Measuring semantic similarity between geospatial conceptual regions. In GeoSpatial semantics-First international conference, GeoS 2005, Vol. 3799 of LNCS (pp. 90-106). Berlin, Germany: Springer.
46. Schwering, A., & Raubal, M. (2005b). Spatial relations for semantic similarity measurement. In Perspectives in conceptual modeling, Vol. 3770 of LNCS (pp. 259-269). Berlin, Germany: Springer.
47. Shepard, R. N. (1982). Structural representations of musical pitch. In D. Deutsch (Ed.), Psychology of music (pp. 343-390). New York: Academic Press.
48. R. N. Shepard 1987 Toward a universal law of generalization for psychological science Science 237 4820 1317 1323 10.1126/science.3629243 912862
49. M. J. Steedman 1977 The perception of musical rhythm and metre Perception 6 5 555 569 10.1068/p060555
50. Thornton, C. (2007). How thinking inside the box can become thinking outside the box. In A. Cardoso & G. Wiggins (Eds.), Proceedings of the 4th international joint workshop on computational creativity.
51. Thornton, C. (2009). Personal communication.
52. S. R. Turner 1995 Margaret Boden, the creative mind Artificial Intelligence Journal 79 145 159 10.1016/0004-3702(95)90029-2
53. Wallas, G. (1926). The art of thought. New York: Harcourt Brace.
54. G. A. Wiggins 2006 A preliminary framework for description, analysis and comparison of creative systems Journal of Knowledge Based Systems 19 7 449 458 10.1016/j.knosys.2006.04.009 (Pubitemid 44557035)
55. G. A. Wiggins 2006 Searching for computational creativity New Generation Computing 24 3 209 222 1108.68550 10.1007/BF03037332
56. Wiggins, G. A., Harris, M., & Smaill, A. (1989). Representing music for analysis and composition. In M. Balaban, K. Ebcioglu, O. Laske, C. Lischka, & L. Soriso (Eds.), Proceedings of the second workshop on AI and music (pp. 63-71). Menlo Park, CA: AAAI.
57. Wiggins, G. A., Pearce, M. T., & Müllensiefenllensiefen, D. (2009). Computational modelling of music cognition and musical creativity. In R. Dean (Ed.), Oxford handbook of computer music and digital sound culture. Oxford: Oxford University Press.
58. R. B. Zajonc 1968 Attitudinal effects of mere exposure Journal of Personality and Social Psychology, Monograph Supplement 9 1 27 10.1037/h0025848