Neural networks
Inspiration derives from neuroscience
- But only remotely similar to real brains
- Typically no spikes
- Typically use implausible constraints or learning rules
Often used where data or functions are uncertain
- Goal is to learn from the data
- And to generalize from learned instances
Key attributes
- Parallel computation
- Learning (networks design themselves)
- Fault tolerance (insensitive to component failures)