A HYBRID MODEL OF REASONING BY ANALOGY

The best mapping is found by evaluating all possible ones in parallel on a competitive basis. This is
done by relaxing the constraint satisfaction network (the LTM extended with the temporarily
constructed nodes and links) using the associative mechanism. Because of the links between the
elements of the target and source descriptions and the correspondence nodes, the activity of all
nodes in LTM influences the activity of the correspondence nodes. What makes this different from
the use of the associative mechanism in the automatic retrieval process is the presence of inhibitory
links in the network. After relaxing the network, we find the best mapping in the following way:
for each slot in the target the most active correspondence node is found (which is the winner on the
basis of the competitive mechanism of relaxing the network) and the link between the map node
and that corresponding node is strengthened to have a weight of 1, while all other competing links
are dropped out. In this way the map node is finally connected only to these correspondence nodes
which form the best mapping.
The relaxing mechanism does not start at any particular moment, because, as it has been pointed
out, the associative mechanism runs continuously, and in this way in each moment its partial
results are available, i.e. at each moment, independently how much semantic or structural
correspondence is established, the first approximation of a best map is present.
Manipulating Input and Goals .
One way of pragmatic control of processing is goal manipulation, i.e. putting forward additional
goals or subgoals (like direct mapping between most active slots) or rejecting some old goals.
Another way of pragmatic control of processing is changing the input nodes. If, for example,
something in the environment is changed then the perceptual mechanism will change the state of
the input nodes (including the case where another reasoner provides some help by drawing
attention to some elements of the target or by presenting additional information). But it is also
possible to consider an active reasoner that may for example re-read a written description of the
current problem which would focus her attention on some particular details, or the reasoner might
perform actions that change the environment and perceive their effects, or she can write down
intermediate results of the reasoning process and then read them back (by redirecting the input
activity), or she can manipulate the environment itself by experimenting and testing certain
hypotheses.
Pragmatic control on the running of processes within mapping .
The mapping process is performed by all those symbolic processes running in parallel. The exact
moment when a symbolic processor is triggered, and both its speed and success heavily depend on
the activity of the node representing this process and on the activity of the nodes which are used as
data by this process. In this way a thorough pragmatic control is established on the way the
mapping process is performed.
Processes of establishing semantic and structural correspondence compete with each other running
in parallel at different speed, and thus at each moment both establishing semantic correspondence
between additional elements and establishing structural correspondence by developing the
connectionist network further (i.e. building new correspondence nodes and links based upon the
existing ones) can continue.
Depending on the results of this competition (i.e. which one will be most active) either more
concrete or more abstract analogies can be reached. Of course, this competition can be partially
influenced by the reasoner by manipulating the input and goal nodes. For example, if a goal to find
an abstract mapping is established, the concept `abstract' and the related concepts (like `object',
`relation', `cause') will be activated. This will enable the semantic process to find general
correspondences (e.g. `John' and `table' being both objects, a property that would not ordinarily