1. The document discusses principles of dog learning that could inform the development of interactive artificial characters that learn effectively. 2. Some key principles discussed include using temporal proximity to constrain causal relationships, representing states and actions hierarchically, and using implicit feedback to guide exploration and learning of perceptual models. 3. The document also emphasizes making learning easy for trainers through techniques like luring and shaping, and assigning credit in a way that matches the trainer's expectations.

1. Learning from how dogs learn Prof. Bruce Blumberg The Media Lab, MIT [email_address] www.media.mit.edu/~bruce

2. About me…

3. About me…

6. sheep|dog:trial by eire See sheep|dog video on my website

7. Object persistence See object persistence video on my website

8. Temporal representation See temporal representation (aka Goatzilla) video on my website

9. Alpha Wolf See alpha wolf video on my website

10. [email_address] See rover@home video on my website or go to Scientific American Frontiers website

11. Dobie T. Coyote Goes to School See Dobie video on my website

14. The problem facing dogs (real and synthetic) Set of all possible actions Set of all motivational goals Set of all possible stimuli What do I do, when, in order to best satisfy my motivational goals?

15. The space of possible stimuli is wicked big Time of Occurence State Space Set of all possible stimuli Smells Motion Sounds Dog sounds Speech Whistles Modality of Stimuli

16. The space of possible actions is also very big Set of all possible actions Action Time of Performance Action Space Figure -8 Shake Low shake High -5 Beg Down Left ear twitch

17. Who gets credit for good things happening? Yumm.. Action Figure -8 Shake High -5 Beg Down Left ear twitch Modality of Stimuli Low shake Motion Sounds Dog sounds Speech Whistles

18. Who gets credit for good things happening? Yumm.. Time stalk grab-bite eye orient kill-bite chase

19. Conventional idea: back propagation from goal stalk grab-bite eye orient kill-bite chase Yumm.. Time Credit flows backward

20. Conventional idea: back propagation from goal stalk grab-bite eye orient kill-bite chase Yumm.. Time Credit flows backward

21. Conventional idea: back propagation from goal stalk grab-bite eye orient kill-bite chase Yumm.. Time Credit flows backward

23. Leyhausen’s suggestion… stalk grab-bite eye orient kill-bite chase Time Each element is innately self-motivating and has innate reward metric motivation & reward motivation & reward motivation & reward motivation & reward motivation & reward motivation & reward

24. Leyhausen’s suggestion… stalk grab-bite eye orient kill-bite chase Time Each element is innately self-motivating and has innate reward metric motivation & reward motivation & reward motivation & reward motivation & reward motivation & reward motivation & reward

25. Coppinger’s suggestion… stalk grab-bite eye orient kill-bite chase Time Varying innate tendency to follow behavior with “next” in sequence

26. Functional goal plays incidental role stalk grab-bite eye orient kill-bite chase Time Propagated value from functional goal plays incidental role Yumm..

29. Dogs constrain search for causal agents Time Consequences Window: Trainer “clicks” signaling reward is coming. When reward is actually received Attention Window: Cue given immediately before or as dog is moving into desired pose Sit Approach Eat Dogs make the problem tractable by constraining search for causal agents to narrow temporal windows

30. Dogs use implicit feedback to guide perceptual learning Sit Time “ sit-utterance” perceived. Approach Eat “ click” perceived. Dog decides to sit Build & update perceptual model of “sit-utterance” Dogs use rewarded action to identify potentially promising state to explore and to guide formation of perceptual models

36. The System

37. Dobie T. Coyote… See dobie video on my website