Connectionist content


Authors
Eric Lormand
University of Michigan, Ann Arbor
Abstract
If the arguments of chapter 1 are correct, associationist connectionist models (such as ultralocal ones) yield the clearest alternatives to the LOT hypothesis. While it may be that such models cannot provide a general account of cognition, they may account for important aspects of cognition, such as low-level perception (e.g., with the interactive activation model of reading) or the mechanisms which distinguish experts from novices at a given skill (e.g., with dependency-network models). Since these models stand a fighting chance of being applicable to some aspects of cognition, it is important from a philosophical standpoint that we have appropriate tools for understanding such models. In particular, we want to have a theory of the semantic content of representations in certain connectionist models. In this chapter, I want to consider the prospects for applying a specific sort of "fine-grained" theory of content to such models
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