Proceedings of the Annual Meeting of the Cognitive Science Society

Connectionism offers greater promise than symbolic approaches to cognitive science for explaining the intentionality of mental states, that is, their ability to be about other phenomena. In symbolic cognitive science symbols are essentially arbitrary so that there is nothing that intrinsically relates them to their referents. The causal process of transduction is inadequate to explain how mental states acquire intentionality, in part because it is incapable of taking into account the contextual character of mental states. In contrast, representations employed in connectionist models can be much more closely connected to the things they represent. The ability to produce these representations in response to external stimuli is controlled by weights which the system acquires through a learning process. In multi-layer systems the particular representations that are formed are also determined by processes internal to the system as it learns to produce the overall desired output. Finally, the representations produced are sensitive both to contextual variations in the objects being represented and in the system doing the representing. These features suggest that connectionism offers significant resources for explaining how representations are about other phenomena and so possess intentionality.