The Connectionist Computational Theory of Mind
While searching for adequate theories of mind one is likely to come across the connectionist version of the computational theory of mind, and it appears that, this particular theory, provides us with working models effortlessly for such cognitive capacities as rapid recognition, associative memory and categorical generalization.
However there are a large number of obstructions to overcome with the connectionist computational theory of mind, and although proponents of it want us to give up on rule-based systems of explanation such as the classicists version, these things need to be rectified before it can be considered a sufficient theory of mind.
Although the connectionist version has a viable approach to association processing it seems to fail on such tasks as language and reasoning. The hindrances range in magnitude from minute to monstrous and include quandaries such as problems with the concept of an individual, the problem of compositionality, the problem of quantification, recursive thoughts/propositional problems, trouble with commonsense questions and last but not least the problem of systematicity.
The problem with the concept of an individual is an painless point to understand but is not so easily solved. If we have a set of identical twins or even something a bit more general like two trees of the same species, height, age etc. the connectionist system is blind to the fact that they are actually separate entities. There are a number of proposed responses to this dilemma but none of them are adequate.
The archetypal property of all our languages is compositionality and this is where another predicament with the connectionist CTM occurs. Representations are built out of parts and have their meaning based on the meanings of all the parts and from the way they are combined. Subsequently, due to the fact that our thoughts are built out of concepts, and are not stored as whole entities within our mind, we encounter major problems and all the attempts to rectify them turn out to be substandard halfway measures. After all, babies eating slugs, and slugs eating babies are two very distinct ideas whose meanings are assembled on the fly using syntax, and even though you may never have seen either sentence before you can understand it with ease.
Systematicity on the other hand seems to be one of the more obtrusive problems the connectionist CTM must face, and was identified by Fodor & Pylyshyn (1988). It states that the ability to think/create/understand a sentence of a particular structure is intrinsically connected to the ability to think/create/understand a sentence that has a related structure, in that, there is no human that can understand the meaning of the sentence “Jason loves Ashley” but fails to understand the concept of “Ashley loves Jason”. Regrettably though, connectionist models, even once they have been trained to recognize one sentence of the previous example, still fail to recognize the second. Systematicity must be guaranteed to work in connectionist models for their theory of mind to be a viable option as this is a key component of human intelligence, and, according to Fodor & Pylyshyn, is a given in the classicists approach.
The connectionist computational theory of mind, although on distant inspection appears to be a much healthier option than other models, seems to have just as many drawbacks as them, and once again, cannot be considered a viable option for a complete theory of mind without at least some of these issues being overcome.
The ones we have discussed would be a good starting point but there are also other smaller, but still very relevant ones that must be addressed. Such as, the length of time it takes to train a connectionist model vs the length of time it takes a human to learn similar tasks, the fact that back propagation in connectionist models appears to ‘cheat’ as there is no evidence of our minds working in such ways and the fact that connectionist models fail to recognize our recursive thoughts i.e. a proposition embedded within another proposition. Until such times as these are solved, the connectionist CTM is promising, but still has a lot of work ahead of it.
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