Cognitive science is an interdisciplinary research endeavor focusing on human cognitive phenomena such as memory, language use, and reasoning. It emerged in the second half of the 20th century and is charting new directions at the beginning of the 21st century. This chapter begins by identifying the disciplines that contribute to cognitive science and reviewing the history of the interdisciplinary engagements that characterize it. The second section examines the role that mechanistic explanation plays in cognitive science, while the third focuses (...) on the importance of mental representations in specifically cognitive explanations. The fourth section considers the interdisciplinary nature of cognitive science and explores how multiple disciplines can contribute to explanations that exceed what any single discipline might accomplish. The conclusion sketches some recent developments in cognitive science and their implications for philosophers. (shrink)

Responses are strengthened by consequences having to do with the survival of individuals and species. With respect to the provenance of behavior, we know more about ontogenic than phylogenic contingencies. The contingencies responsible for unlearned behavior acted long ago. This remoteness affects our scientific methods, both experimental and conceptual. Until we have identified he variables responsible for an event, we tend to invent causes. Explanatory entities such as “instincts,” “drives,” and “traits” still survive. Unable to show how organisms can behave (...) effectively under complex circumstances, we endow them with special abilities permitting them to do so.Behavior exhibited by most members of a species is often accepted as inherited if all members were not likely to have been exposed to relevant ontogenic contingencies. When contingencies are not obvious, it is perhaps unwise to call any behavior either inherited or acquired, as the examples of churring in honey guides and following in imprinted ducklings show. Nor can the relative importance of phylogenic and ontogenic contingencies be argued from instances in which unlearned or learned behavior intrudes or dominates. Intrusions occur in both directions.Behavior influenced by its consequences seems directed toward the future, but only past effects are relevant. The mere fact that behavior is adaptive does not indicate whether phylogenic or ontogenic processes have been responsible for it. Examples include the several possible provenances of imitation, aggression, and communication. The generality of such concepts limits their usefulness. A more specific analysis is needed if we are to deal effectively with the two kinds of contingencies and their products. (shrink)

This paper discusses different approaches incognitive science and artificial intelligenceresearch from the perspective of radicalconstructivism, addressing especially theirrelation to the biologically based theories ofvon Uexküll, Piaget as well as Maturana andVarela. In particular recent work in New AI and adaptive robotics on situated and embodiedintelligence is examined, and we discuss indetail the role of constructive processes asthe basis of situatedness in both robots andliving organisms.

Despite the growing popularity of nonrepresentationalist approaches to cognition, and especially of those coming from the enactivist corner, positing internal representations is still the order of the day in mainstream cognitive science. Indeed, the idea that we have to invoke internal content-carrying, thing-like entities to account for the workings of mind and cognition proves to be particularly resilient. In this paper, my aim is to explain at least partially where this resilience of the reified notion of representation comes from. What (...) I want to show is that, crucially, positing inner representations isn’t so much warranted by the scientific practice itself – as is commonly held – but much more motivated by nonscientific and pre-theoretical elements that largely stem from, what I will call, linguistic contingencies. Otherwise put, much of what makes the reified notion of representation an attractive posit can be explained, not by the science, but by the way we, including cognitive scientists, speak. What I want to do here, then, is first, rehearse what reification means in the context of representationalism and, second, specify which linguistic contingencies can account for why the idea of positing representations remains for many not only a viable option, but an indispensability for anyone interested in explanations of mind and cognition. (shrink)

According to the theory of internal working model, belief in altruistic human nature positively influences prosocial behavior. However, the precise influencing mechanism remains unclear. Based on the determinants of human behavior theory and self-efficacy theory, we hypothesized that belief in altruistic human nature indirectly influences prosocial behavior through causally linked multiple mediators of prosocial attitude and prosocial self-efficacy. The results of the current research supported our hypothesis and demonstrated that this serial mediation model could be generalized across individualistic and collectivistic (...) cultures. (shrink)

What features will something have if it counts as an explanation? And will something count as an explanation if it has those features? In the second half of the 20th century, philosophers of science set for themselves the task of answering such questions, just as a priori conceptual analysis was generally falling out of favor. And as it did, most philosophers of science just moved on to more manageable questions about the varieties of explanation and discipline-specific scientific explanation. Often, such (...) shifts are sound strategies for problem-solving. But leaving fallow certain basic conceptual issues can also result in foundational debates. (shrink)

Clark has recently suggested that predictive processing advances a theory of neural function with the resources to put an ecumenical end to the “representation wars” of recent cognitive science. In this paper I defend and develop this suggestion. First, I broaden the representation wars to include three foundational challenges to representational cognitive science. Second, I articulate three features of predictive processing’s account of internal representation that distinguish it from more orthodox representationalist frameworks. Specifically, I argue that it posits a resemblance-based (...) representational architecture with organism-relative contents that functions in the service of pragmatic success, not veridical representation. Finally, I argue that internal representation so understood is either impervious to the three anti-representationalist challenges I outline or can actively embrace them. (shrink)

I identify three lessons from Kenneth Craik’s landmark book “The Nature of Explanation” for contemporary debates surrounding the existence, extent, and nature of mental representation: first, an account of mental representations as neural structures that function analogously to public models; second, an appreciation of prediction as the central component of intelligence in demand of such models; and third, a metaphor for understanding the brain as an engineer, not a scientist. I then relate these insights to discussions surrounding the representational status (...) of predictive processing – which, I argue, provides a contemporary vindication of Craik’s extremely prescient “hypothesis on the nature of thought.”. (shrink)

We argue that one important aspect of the “cognitive neuroscience revolution” identified by Boone and Piccinini :1509–1534. doi: 10.1007/s11229-015-0783-4, 2015) is a dramatic shift away from thinking of cognitive representations as arbitrary symbols towards thinking of them as icons that replicate structural characteristics of their targets. We argue that this shift has been driven both “from below” and “from above”—that is, from a greater appreciation of what mechanistic explanation of information-processing systems involves, and from a greater appreciation of the problems (...) solved by bio-cognitive systems, chiefly regulation and prediction. We illustrate these arguments by reference to examples from cognitive neuroscience, principally representational similarity analysis and the emergence of dynamical models as a central postulate in neurocognitive research. (shrink)

Tribunals have come to depend increasingly on expertise for determining the facts in cases. However, current legal methods have proved problematic to work with. This paper argues that, as a special model of public understanding of science, assessing expertise should consider source credibility of expertise from internal aspects, including scientific validity and reliability, and external aspects involving the credibility of experts. Using the Carneades Argumentation System we show that the internal and the external aspects are mediated by the structure of (...) the argument from expert opinion with its matching set of critical questions. (shrink)

This commentary elaborates on Gray's conclusion that his neurophysiological model of consciousness might explain how consciousness arises from the brain, but does not address how consciousness evolved, affects behaviour or confers survival value. The commentary argues that such limitations apply to all neurophysiological or other third-person perspective models. To approach such questions the first-person nature of consciousness needs to be taken seriously in combination with third-person models of the brain.

On the basis of neuropsychological evidence, it is clear that attention should be given a role in any model of consciousness. What is known about the many instances of dissociation between explicit and implicit knowledge after brain damage suggests that conscious experience might not be linked to a restricted area of the brain. Even if it were true that there is a single brain area devoted to consciousness, the subicular area would seem to be an unlikely possibility.