:orphan:

alpha_vss
*********

**Note:** Only applicable in the Rescorla-Wagner mechanism.

Specifies the learning rate for vss-values (the associative strength between pairs of stimulus elements),
used in the updating of ``vss``-values.

The parameter ``alpha_vss`` can be set to certain values for certain particular element-element pairs.
It can also be specified as a single value, in which case the same learning rate is used for all
element-element pairs.

Syntax
------

::

  alpha_vss = e1->e2: v1, e3->e4: v2, ..., default: d
  alpha_vss = v1

where ``v1,v2,...,vn`` are :ref:`scalar expressions<scalar-expressions>`.

Description
-----------

``alpha_vss = e1->e2: v1, e3->e4: v2, ..., default: d`` sets the learning rate for

- vss(e1->e2) to v1,
- vss(e3->b4) to v2, ...,

and the learning rate for all other vss-values to d.

- The specification is independent of the list order:

  ``e1->e2: v1, e3->b4: v2, default: d``

  is the same as

  ``e3->e4: v2, default: d, e1->e2: v1``.

- ``default`` need not be specified if all possible combinations ``element->element`` are present in the list. For example,

  ::

    stimulus_elements = e1, e2
    alpha_vss = e1->e1:v11, e1->e2:v12, e2->e2:v22

----

``alpha_vss = v1`` sets the learning rate for all vss-values to v1.

- ``alpha_vss = v1`` is the same as ``alpha_vss = default: v1``.

Dependencies
------------

- The property ``stimulus_elements`` must be specified before ``alpha_v``.
- Each stimulus element used in the specification of ``alpha_vss`` must be present in the parameter ``stimulus_elements``.
- Applicable only in the Rescorla-Wagner mechanism. (Use ``alpha_v`` in other mechanism.)

Examples
--------

::

  @variables x = 1
  alpha_vss = element1->element2: x, element3->element4: x+1, default:x+2

sets the learning rate for vss(element1->element2) to 1 and for vss(element3->element4) to 2, and
for the remaining possible element-element pairs to 3.

::

  alpha_vss = element1->element2: 0.5, default:0

sets the initial value for v(element1->element2) to 0.5, and for the remaining possible element-element pairs to 3.

::

  alpha_vss = 0.1

sets the learning rate for all v-values to 0.1.
