An automaton framework for neural nets that learn

Brindley (1967, 1969, 1972) has discussed nets of several types of formal neurons, many of whose functions are modifiable by their own input stimuli. Because Brindley's results are widely referred to, for example Marr (1970, 1971) and include some of the scarce non-trivial theorems on learning nets, it is important that serious side-conditions be made explicit. The language of finite automata is used to mathematicize the problem of adaptation sufficiently to remove some ambiguities of Brindley's approach. We close the paper by relating our framework to other formal studies of adaptation.