1 / 23

PSY105 Neural Networks 1/5 NEWS FLASH: Lab Class cancelled on 31/10/31 due to strike

PSY105 Neural Networks 1/5 NEWS FLASH: Lab Class cancelled on 31/10/31 due to strike. 1. “Patterns emerge”. π. Pin board. Ball bearing. Path of the ball. Ledge. A physical example .

gunnar
Download Presentation

PSY105 Neural Networks 1/5 NEWS FLASH: Lab Class cancelled on 31/10/31 due to strike

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. PSY105 Neural Networks 1/5NEWS FLASH: Lab Class cancelled on 31/10/31 due to strike 1. “Patterns emerge”

  2. π

  3. Pin board Ball bearing Path of the ball Ledge A physical example Pin board is at a steep angle. The ball is let loose in the centre at the top and rolls through the pins to come to rest on the ledge

  4. The Galton Machine http://www.ms.uky.edu/~mai/java/stat/GaltonMachine.html

  5. Final distribution after many trials is approximately normal (approximation improves with increasing number of trials)

  6. Flocking starlings http://www.youtube.com/watch?v=4DKtj4E_iss

  7. Flocking starlings

  8. Boids http://www.youtube.com/watch?v=rN8DzlgMt3M

  9. Boids

  10. Boids Three rules, followed by individuals: • separation: steer to avoid crowding local flockmates • alignment: steer towards the average heading of local flockmates • cohesion: steer to move toward the average position of local flockmates Reynolds, C.(1987), Flocks, herds and schools: A distributed behavioral model, SIGGRAPH '87: Proceedings of the 14th annual conference on Computer graphics and interactive techniques (Association for Computing Machinery): 25--34, doi:10.1145/37401.37406, ISBN 0-89791-227-6

  11. ‘Pond’ Simulation Red turtles and green turtles get along. But each turtle wants to make sure it lives near some of its “own”.

  12. Emergence Turtles, Termites, and Traffic Jams : Explorations in Massively Parallel Microworlds by MitchelResnick

  13. Levels of description affect both the objects we use and the answers we seek when we investigate the brain

  14. A hierarchy of levels in the mind/brain? Perhaps the incredibly complex patterns of neural firings that occur in the brain also have higher-level descriptions in terms of information processing that is going on in the mind Mental structures Goals, Beliefs, Concepts “Language of thought” ?? Lower level implementations ?? The brain

  15. Focus on: neurons Neurons are the cells of the brain. They appear to be integrating or combining many thousands of signal sources (from other neurons) to produce new signals Each orange dot in the photo is a synapse (input)

  16. …And how do you decide if a feature is key What are the key features of a neuron?

  17. Membrane potential (due to combined signal input) Threshold forfiring Increasing due to overall excitatory influence time Generation of action potentials Action potentials

  18. Incoming action potential Large excitatory PSP is one of Small excitatory Axon terminal Small inhibitory dendrite Large inhibitory Generation of PSPs

  19. Warren McCullock 1943 - First artificial neuron model Warren McCulloch (neurophysiologist) Walter Pitts (mathematician)

More Related