Normative theories provide essential tools for understanding behaviour, not just for reasoning, judgement, and decision-making, but many other areas of cognition as well; and their utility extends to the development of process theories. Furthermore, the way these tools are used has nothing to do with the is-ought fallacy. There therefore seems no basis for the claim that research would be better off without them.

One of the most striking features of “Bayesian rationality” is the detail with which behavior on logical reasoning tasks can now be predicted and explained. This detail is surprising, given the state of the field 10 to 15 years ago, and it has been brought about by a theoretical program that largely ignores consideration of cognitive processes, that is, any kind of internal behavior that generates overt responding. It seems that an increase in explanatory power can be achieved by restricting a psychological theory.

the term “moral heuristic” as used by sunstein seeks to bring together various traditions. however, there are significant differences between uses of the term “heuristic” in the cognitive and the social psychological research, and these differences are accompanied by very distinct evidential criteria. we suggest the term “moral heuristic” should refer to processes, which means that further evidence is required.

The key weakness of the proposed distinction between rules and similarity is that it effectively converts what was previously seen as a consequence of rule or similarity-based processing, into a definition of rule and similarity themselves – evidence is elevated into a conceptual distinction. This conflicts with fundamental intuitions about processes and erodes the relevance of the debate across cognitive science.

Shanker & King (S&K) fail to provide substantive reasons for a paradigm shift in the study of communication because nonstandard and equivocal use of terminology obscures and undercuts their arguments.

Clahsen's experimental data from generalization, frequency, and priming fail to support and even conflict with those aspects of his dual-route account that distinguish it from schema theories.

Rethinking innateness is a timely volume which forcefully demonstrates the importance of modelling in understanding development, ‘innateness’, and the nature of change. It provides an inspiring vision of what developmental psychology could one day be like, linking behaviour and biology via connectionist models. However, Rispoli's worry about the book's potential for detrimental polarization does not seem unfounded. One aspect of the book that deserves comment in this respect is the focus on connectionism to the exclusion of other types of model. It is unclear from Rethinking innateness itself whether this exclusion of other approaches merely stems from the legitimate desire to write a focused book, or whether it possibly reflects an actively held view that connectionism is the one true approach to modelling development. Regardless of the authors' intentions, the role of connectionism in relation to other computational approaches is an issue which is particularly pertinent to the study of language acquisition.

To clarify straightaway, I not only concur with Elman et al. on the central role of modelling, but also strongly believe that the task of the cognitive scientist is not complete until one has an account of how a particular process is realised in a neural architecture. These two commitments give connectionist models a central role. But they do not make connectionism the exclusive modelling tool for the study of language acquisition, nor necessarily the best path to currently pursue. The reasons for this are twofold.

The first is a matter of research strategy. It is possible that more rapid progress and greater success might be made if one starts with high-level models which give less immediate regard to matters of implementation.

Van Gelder's specification of the dynamical hypothesis does not improve on previous notions. All three key attributes of dynamical systems apply to Turing machines and are hence too general. However, when a more restricted definition of a dynamical system is adopted, it becomes clear that the dynamical hypothesis is too underspecified to constitute an interesting cognitive claim.

We argue that the notion of distal similarity on which Edelman's reconstruction of the process of perception and the nature of representation rests is ill defined. As a consequence, the mapping between world and description that is supposedly at stake is, in fact, a mapping between two different descriptions or “representations.”

The Schyns et al. target article demonstrates that different classifications entail different representations, implying “flexible space learning.” We argue that flexibility is required even at the within-category level.