Talk presented to undergraduate Computer Science students at the University of Exeter (Feb 2009)

1. Babies and Computers Are They Related? – Abel Nyamapfene

2. Abstract: Current opinion suggests that language is a cognitive process in which different modalities such as perceptual entities, communicative intentions and speech are inextricably linked. In this talk I discuss my belief that the problems psychologists are grappling with in child development are also the same problems computer scientists working in artificial intelligence and robotics are facing. I show how computational modelling, in conjunction with the availability of empirical data, has contributed to our understanding of child language acquisition, and how this knowledge has advanced progress in robotics.

3. Psychologist How do babies learn life skills? How can you be as adaptive as a baby? Computer Scientist

7. Examples humanoids Games Medical Diagnostics Weapons of War Education

13. Models of Development Based on Brain Neural Processing Actual Neurons : Complex

14. Models of Development Based on Brain Neural Processing Artificial Neurons : Very Very Simplified

15. Some Models of One-Word Child Language “ Dada” instead of “Here comes Daddy.” “ Uh oh” instead of “I am happy.” “ More” instead of “Give me some more”

16. 1 : A multilayer perceptron network for mapping images to text (Plunkett et al, 1992). Network by Plunkett et al simulates word – image association and exhibits same developmental learning as a child, but learning mechanism not biologically feasible Image (input) Image (output) Label representation Label (output) Label (input) Image representation joint internal representation

17. 2: Hebbian-linked Self –Organising Architecture Li, Farkas & MacWhinney (2004) Perceptual Input Speech Input Network was inspired by the belief that Brain Modules are interlinked. It successfully simulates Word-Object Mapping in children activated neuron Unidirectional links from Perception to Speech Neuron Layers Second SOM First SOM Unidirectional links from Speech and Perception Neuron Layers

18. 3: An Approach that can associate Two Input Types: - Full counterpropagation network ( Hecht-Nielsen,1987) x input layer x output layer cluster layer y input layer y output layer Z 1 Z 2 Z N

19. 4: Extending the Counterpropagation Approach to Modelling Child Language (Nyamapfene &Ahmad, 2007) Perceptual Input Speech Input Modal weights Competitive Neuron layer Intentional Input Model based on empirical evidence that children have intentions and that brain has multimodal neurons

22. 5: A Control-Theoretic Neural Multi-Net Model of Child Language Acquisition (Nyamapfene, 2008) Environment Desires Emotions Drive Communicative intentions Single-Word Utterance Caregiver response Goals Block diagram of a control systems approach to modelling child language at the one-word early child language acquisition stage Child

25. Finally: Yes, I Think Babies and Computers are Related Thank You!!??!!