New trends in Cognitive Science: Integrative approaches to learning and development

Neurocomputing

Volumn 70, Issue 13-15, 2007, Pages 2139-2147

  Deák, Gedeon O ^a   Bartlett, Marni Stewart ^b   Jebara, Tony ^c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^c Department of Earth and Environmental Sciences   (United States)

Author keywords

Active vision; Brain development; Cognitive development; Cognitive Science; Embodied cognition; Emergent properties; Ethnography; Interdisciplinary research; Language learning; Learning algorithms; Machine learning; Modeling; Social communication

Indexed keywords

ACCURACY; ALGORITHM; ARTIFICIAL INTELLIGENCE; BRAIN DEVELOPMENT; COGNITION; COMPUTER ANALYSIS; COMPUTER INTERFACE; COMPUTER MODEL; COMPUTER SYSTEM; EDITORIAL; FACE PROFILE; INFORMATION PROCESSING; LEARNING; PREDICTION; PRIORITY JOURNAL; ROBOTICS;

EID: 34249663433     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2006.06.008     Document Type: Editorial

References (63)

1. Anisfeld M. Only tongue protrusion is matched by neonates. Dev. Rev. 16 (1996) 149-161
2. R. Baillargeon, The object concept revisited: New directions in the investigation of infants' physical knowledge, in: C. Granrud (Ed.), Visual Perception and Cognition in Infancy, Erlbaum, Hillsdale, NJ, 1993, pp. 265- 315.
3. Baldwin D.A. Understanding the link between joint attention and language. In: Moore C., and Dunham P. (Eds). Joint Attention: Its Origins and Role in Development (1995), Erlbaum, Hillsdale, NJ
4. Ballard D. Principles of animate vision. Artif. Intell. 48 (1991) 57-86
5. Bell A.J., and Sejnowski T.J. An information maximization approach to blind separation and blind deconvolution. Neural Comput. 7 6 (1995) 1129-1159
6. Berger A., Della Pietra S., and Della Pietra V. A maximum entropy approach to natural language processing. Comput Linguistics 22 (1996)
7. A. Borovsky, J.L. Elman, Language input and semantic categories: a relation between cognition and early word learning, J. Child Lang., in press.
8. Bowerman M. Starting to talk worse: clues to language acquisition from children's late speech errors. In: Strauss S. (Ed). U-shaped Behavioral Growth (1982), Academic Press, New York
9. Breazeal C. Emotion and sociable humanoid robots. Int. J. Hum.-Comput. Stud. 59 (2003) 119-155
10. Breazeal C., and Scassellati B. Robots that imitate humans. Trends Cogn. Sci. 8 (2002) 481-487
11. N. Butko, I. Fasel, J. Movellan, Learning about humans during the first 6 minutes of life, in: International Conference on Development and Learning, Bloomington, Indiana, June 2006.
12. Christensen W.D., and Hooker C.A. An interactivist-constructivist approach to intelligence: self-directed anticipative learning. Philos. Psychol. 13 (2000) 5-45
13. Clark A. Being There: Putting Brain, Body, and World Together Again (1997), MIT Press, Cambridge, MA
14. Cohn F., Matias R., Tronick E.Z., Connell D., and Lyons-Ruth D. Face-to-face interactions of depressed mothers and their infants. In: Tronick E., and Field T. (Eds). Maternal Depression and Infant Disturbance (1986), Jossey-Bass, San Francisco 31-45
15. Crain S. 1991 Language acquisition in the absence of experience. Brain Behav. 14 (1991) 597-611
16. Crowley K., Shrager J., and Siegler R.S. Strategy discovery as a competitive negotiation between metacognitive and associative mechanisms. Dev. Rev. 17 (1997) 462-489
17. Damasio A.R. Descartes' Error: Emotion, Reason, and the Human Brain (1994)), Putnam, New York
18. Deák G.O. Chasing the fox of word learning: why "constraints" fail to capture it. Dev. Rev. 20 (2000) 29-80
19. G. Deák, A. Krasno, H. Jasso, Y. You, Watch the hands: infants learn gaze-following from parents' pointing and manual actions, Presented at the XVth Biennial International Conference on Infant Studies, Kyoto, Japan, June 2006.
20. Y. Demiris, A. Dearden, From motor babbling to hierarchical learning by imitation: a robot developmental pathway, in: Proceedings of the Fifth International Workshop on Epigenetic Robotics, Lund University, Cogn. Stud. 123 (2005) 31-37.
21. Elman J.L. Connectionist models of cognitive development: where next?. Trends Cogn. Sci. 9 (2005) 111-117
22. Elman J., Bates E., Johnson M.H., Karmiloff-Smith A., Parisi D., and Plunkett K. Rethinking Innateness: A Connectionist Perspective on Development (1996), MIT Press, Cambridge, MA
23. Fernald A., and Mazzie C. Prosody and focus in speech to infants and adults. Dev. Psychol. 27 (1991) 209-221
24. T. Fumihide, J. R. Movellan, The RUBI Project: designing everyday robots by immersion, in: International Conference on Development and Learning, Bloomington, Indiana, June 2006.
25. Gauthier I., Tarr M.J., Anderson A.W., Skudlarksi P., and Gore J.C. Activation of the middle fusiform face area increases with expertise in recognizing novel objects. Nat. Neurosci. 2 (1999) 568-573
26. J.J. Gibson, An ecological approach to visual perception (1979).
27. Girosi F., Jones M., and Poggio T. Regularization theory and neural network architectures. Neural Comput. 7 (1995) 219-269
28. Heckerman D. A tutorial on learning with Bayesian networks. In: Jordan M. (Ed). Learning in Graphical Models (1999), MIT Press, Cambridge, MA
29. Hung C.P., Kreiman G., Poggio T., and DiCarlo J.J. Fast readout of object identity from Macaque inferior temporal cortex. Science 310 (2005)
30. Hutchins E. Cognition in the Wild (1995), MIT, Cambridge, MA
31. Jebara T. Machine Learning: Discriminative and Generative (2004), Kluwer Academic, Dordrecht
32. Johnson M.K. Developmental Cognitive Neuroscience (1997), Blackwell, Hove, UK
33. Jones S.S. Imitation or exploration. Child Dev. 67 (1996) 1952-1969
34. S.S. Jones, Infants learn to imitate by being imitated, in: International Conference on Development and Learning, Bloomington, Indiana, June 2006.
35. Kaelbling L.P., and Littman M.L. Reinforcement learning: a survey. J. Artif. Intell. Res. 4 (1996)
36. Karmilloff-Smith A. Development itself is the key to understanding developmental disorders. Trends Cogn. Sci. 2 (1998) 389-398
37. Lee T.S., and Yu S.X. An information-theoretic framework for understanding saccadic eye movements. In: Solla S.A., Leen T.K., and Müller K.-R. (Eds). Advances in Neural Information Processing Systems vol. 12 (2000), MIT Press, Cambridge, MA 834-840
38. J.D. Lewis, J.L. Elman, A connectionist investigation of linguistic arguments from poverty of the stimulus: learning the unlearnable, in: Proceedings of the 23rd Annual Conference of the Cognitive Science Society, 2001, pp. 552-557.
39. Markman E.M. Constraints on word meaning in early language acquisition. Lingua 92 (1994) 199-227
40. Meltzoff A.N., and Moore M.K. Persons and representation: why infant imitation is important for theories of human development. In: Nadel J., and Butterworth G. (Eds). Imitation in Infancy (1999), CUP, Cambridge, UK 9-35
41. Movellan J.R., and Watson J.S. The development of gaze following as a Bayesian systems identification problem. Int. Conf. Dev. Learning 2 (2002) 34-40
42. J. Pearl, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, Morgan Kaufmann, 1997.
43. A. Pentland, Are we one? On the nature of human intelligence, in: International Conference on Development and Learning, Bloomington, Indiana, June 2006.
44. Praetorius N. Inconsistencies in the assumptions of constructivism and naturalism: an alternative view. Theory Psychol. 13 (2003) 511-539
45. Pullum G.K., and Scholz B.C. Empirical assessment of stimulus poverty arguments. Linguistic Rev. 19 (2002) 9-50
46. Quartz S.R., and Sejnowski T.J. The neural basis of cognitive development: a constructivist manifesto. Behav. Brain Sci. 20 (1997) 537-596
47. Regier T., and Gahl S. Learning the unlearnable: the role of missing evidence. Cognition 93 (2004) 147-155
48. Renninger L., Walker, Coughlan J., Verghese P., and Malik J. An information maximization model of eye movements. In: Saul L.K., Weiss Y., and Bottou L. (Eds). Advances in Neural Information Processing Systems vol. 17 (2005), MIT Press, Cambridge, MA 1121-1128
49. Rissanen J. Modeling by the shortest data description. Automatica 14 (1978)
50. B. Rogoff, J. Mistry, A. Goncu, and C. Mosier, Guided participation in cultural activities by toddlers and caregivers, Monographs of the Society for Research in Child Development, vol. 58 (7, Serial No. 236), 1993.
51. Schaal S., Ijspeert A., and Billard A. Computational approached to motor learning by imitation. Philos. Trans. R. Soc. London B 358 (2003) 537-547
52. Schlesinger M., and Parisi D. The agent-based approach: a new direction for computational models of development. Dev. Rev. 21 (2001) 121-146
53. T. R. Shultz, F. Rivest, L. Egri, J. Thivierge. Knowledge-based learning with KBCC, in: International Conference on Development and Learning, Bloomington, Indiana, June 2006.
54. Simoncelli E., and Olshausen B. Natural image statistics and neural representation. Ann. Rev. Neurosci. 24 (2001) 1193-1216
55. L.B. Smith, Why development matters, in: International Conference on Development and Learning, Bloomington, Indiana, June 2006.
56. Spelke E. Initial knowledge: six suggestions. Cognition 50 (1994) 431-445
57. Sprague N., and Ballard D. Eye movements for reward maximization. In: Thrun S., Saul L., and Scholkpf B. (Eds). Advances in Neural Information Processing Systems vol. 16 (2003), MIT Press, Cambridge, MA
58. Sutton R., and Barto A. Reinforcement Learning (1998), MIT Press, Cambridge, MA
59. Tomasello M. The Cultural Origins of Human Cognition (1999), Harvard, Cambridge, MA
60. Triesch J., Teuscher C., Deák G., and Carlson E. Gaze-following: why (not) learn it?. Dev. Sci. 9 (2006) 125-147
61. Vapnik V. Statistical Learning Theory (1998), Wiley, New York
62. Watson J. Smiling, cooing, and the game. Merrill-Palmer Quart. 18 (1972) 323-339
63. Yoshida W., and Ishii S. Resolution of uncertainty in prefrontal cortex. Neuron 50 5 (2006) 781-789