*Experiment 1:*
off-line,
, ,
local input representation,
3 hidden units per predictor,
4 hidden units shared among the representational modules.
10 test runs with 10,000 epochs for the
representational modules were conducted.
In 7 cases
the system found a binary
factorial code: In the end, one of the output units always emitted
a constant value.
In the remaining 3 cases, the code was at least binary and invertible.

*Experiment 2:*
off-line,
, ,
local input representation,
3 hidden units per predictor,
4 hidden units shared among the representational modules.
10 test runs with 10,000 epochs for the
representational modules were conducted.
In 5 cases
the system found a binary
factorial code: In the end, two of the output units always emitted
a constant value.
In the remaining cases, the code did not use the minimal number
of output units but was at least binary and invertible.

*Experiment 3:*
on-line,
, ,
distributed input representation,
2 hidden units per predictor,
4 hidden units shared among the representational modules.
10 test runs with 250,000 pattern
presentations were conducted.
This was sufficient to always find a quasi-binary
factorial code: In the end, two of the output units always emitted
a constant value. In 7 out of 10 cases, less than 100,000 pattern
presentations (corresponding to 25,000 epochs) were necessary.

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