A less radical alternative to the eliminativist position, termed the subsymbolic hypothesis, was proposed by Smolensky (1988), to the effect that mental processing cannot be fully and accurately described in terms of symbol manipulation, requiring instead a description at the level of subsymbolic features, where these features are represented in a distributed way in the network. Such a view does not preclude the possibility that assemblies of units in a connectionist system do in fact encode symbols and more complex entities built out of symbols, such as predications and rules. It merely denies that the behavior engendered by these assemblies can be adequately modelled as symbol manipulation. In fact, much of the neural net research over the past two or three decades has sought to understand how neural nets can encode symbolic information (e.g., see Smolensky et al. 1992; Browne and Sun 2001). 