Appendix C: Description of the Associative Networks
In the associative network shown in Figure 3, the
connections Vi,j and Vj,i between the
neuron representing place (or region) i (where the agent is
located) and each neuron representing neighboring places (or
regions) j are updated as follows
= Vj,i = 1 if place or region j
can be accessed from place or region i,
= Vj,i = 0 otherwise
At each location, the Motivation
System activates the desired goal (e.g., unvisited places or
regions), and the goal activates Place (Region) j where it is
= Wi,h Goal h
spreads through the network by using the following equation
= η Σi Vi,j pi
When the location (Place or
Region) of the agent is activated or the number of iterations is
greater than R, the maximum number of iterations the spreading
of activation stops. The activation of all neurons represents a
gradient that is used for planning a path to the closest goal.
For each place m, this is accomplished by choosing
Next Place (Region) = Maxn pn
where n denotes a neighbor of place
Equation 4 ensures that the agent will move in the direction of the
nearest goal if all goals are of the same magnitude. When several
neighboring places i have an identical Goal value, priorities are
used to decide the next place. Priorities are given in the following
order: North, West, East, North-West, North-East, South,
South-West, and South-East.
Parameter η, (η = .5) which controls the attenuation at each
reinjection in the network, was chosen to obtain an adequate signal
at the neurons representing the goal(s). R, the maximum number of
reinjections, (R= 625) was selected to ensure that the
representation of the location of the agent is activated from any
place in the environment where the goal can be found.
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