Computational models fail to shed light on general metaphysical questions concerning the nature of emergence. At the same time, they may provide plausible explanations of particular cases of emergence. This paper outlines the kinds of modest explanations to which computational models are suited. Read more here: Computational Models of Emergent Properties
Rather than taking the ontological fundamentality of an ideal microphysics as a starting point, this article sketches an approach to the problem of levels that swaps assumptions about ontology for assumptions about inquiry. These assumptions can be implemented formally via computational modeling techniques that will be described below. It is argued that these models offer a way to save some of our prominent commonsense intuitions concerning levels. This strategy offers a way of exploring the individuation of higher level properties in a systematic and formally constrained manner.
This paper challenges arguments that systematic patterns of intelligent behavior license the claim that representations must play a role in the cognitive system analogous to that played by syntactical structures in a computer program. In place of traditional computational models, I argue that research inspired by Dynamical Systems theory can support an alternative view of representations. My suggestion is that we treat linguistic and representational structures as providing complex multi-dimensional targets for the development of individual brains. This approach acknowledges the indispensability of the intentional or representational idiom in psychological explanation without locating representations in the brains of intelligent agents.
Read more here: Explanation, Representation and the Dynamical Hypothesis