It's not just that neural nets
are good at classifying pictures of hot dogs or whatever: they seem able to build representations of ideas.
At the initial stage of functioning of the artificial life, the neural net
weights of agents are initialized by some random values (the behavior of the players is chaotic and senseless; their impacts with the ball are unpredictable).
The results reported here derive exclusively from analyses based on standard neural nets
using backpropagation based on standard logistic squashing, momentum, and varying learning rates (cf.
A neural net
analysis of 45 SEC targeted firms over the period 2000 to 2005 indicated that such announcements did not have an adverse impact on stock price both at the time of the announcement and six months later.
map information from one or more input nodes into an output node (equivalent to a regressand).
Petroni outline a model of epileptic phenomena grounded on the correlation processes in cellular neural nets
, providing a further connection between neural nets
theory and the actual possibility of applying it in diagnostics.
Those who have used neural nets
and inductive learning for intrusion detection and for research found them to be successful and effective, Chu said.
The neural nets
developed in this research are equivalent to templates for market based, capitalist economies.
The particular statistical tool that seems most appropriate for this task is the neural net
(Neural Networks, Laurene Fausett, Prentice Hall, 1994).
are already good at recognizing objects and people in photographs.
learn by training, not by being programmed.
In that event, it would take information about both neural nets
and cell biology to understand and to artificially create a conscious mind.