Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Combining Hebbian and reinforcement learning in a minibrain model   A toy model of a neural network in which both Hebbian learning and
reinforcement learning occur is studied. The problem of `path interference',
which makes that the neural net quickly forgets previously learned input-output
relations is tackled by adding a Hebbian term (proportional to the learning
rate $\eta$) to the reinforcement term (proportional to $\rho$) in the learning
rule. It is shown that the number of learning steps is reduced considerably if
$1/4 < \eta/\rho < 1/2$, i.e., if the Hebbian term is neither too small nor too
large compared to the reinforcement term.

25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
1
The categories of this paper are: cs
31
The categories of this paper are: ao-sci