Self-organization in a simple brain model
- Brookhaven National Lab., Upton, NY (United States). Dept. of Physics
- Niels Bohr Inst., Copenhagen (Denmark). Dept. of Physics
Simulations on a simple model of the brain are presented. The model consists of a set of randomly connected neurons. Inputs and outputs are also connected randomly to a subset of neurons. For each input there is a set of output neurons which must fire in order to achieve success. A signal giving information as to whether or not the action was successful is fed back to the brain from the environment. The connections between firing neurons are strengthened or weakened according to whether or not the action was successful. The system learns, through a self-organization process, to react intelligently to input signals, i.e. it learns to quickly select the correct output for each input. If part of the network is damaged, the system relearns the correct response after a training period.
- Research Organization:
- Brookhaven National Lab. (BNL), Upton, NY (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC02-76CH00016
- OSTI ID:
- 34409
- Report Number(s):
- BNL-61443; CONF-9406191-2; ON: DE95008312; TRN: AHC29511%%119
- Resource Relation:
- Conference: World congress on neural networks, San Diego, CA (United States), 4-9 Jun 1994; Other Information: PBD: 10 Mar 1994
- Country of Publication:
- United States
- Language:
- English
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