The computational paradigm, which has dominated psychology and artificial intelligence since the cognitive revolution, has been a source of intense debate. Recently, several cognitive scientists have argued against this paradigm, not by objecting to computation, but rather by objecting to the notion of representation. Our analysis of these objections reveals that it is not the notion of representation per se that is causing the problem, but rather specific properties of representations as they are used in various psychological theories. Our analysis (...) suggests that all theorists accept the idea that cognitive processing involves internal information-carrying states that mediate cognitive processing. These mediating states are a superordinate category of representations. We discuss five properties that can be added to mediating states and examine their importance in various cognitive models. Finally, three methodological lessons are drawn from our analysis and discussion. (shrink)

Representation is a central part of models in cognitive science, but recently this idea has come under attack. Researchers advocating perceptual symbol systems, situated action, embodied cognition, and dynamical systems have argued against central assumptions of the classical representational approach to mind. We review the core assumptions of the dominant view of representation and the four suggested alternatives. We argue that representation should remain a core part of cognitive science, but that the insights from these alternative approaches must be incorporated (...) into models of cognitive processing. (shrink)

Advocates of dynamic systems have suggested that higher mental processes are based on continuous representations. In order to evaluate this claim, we first define the concept of representation, and rigorously distinguish between discrete representations and continuous representations. We also explore two important bases of representational content. Then, we present seven arguments that discrete representations are necessary for any system that must discriminate between two or more states. It follows that higher mental processes require discrete representations. We also argue that discrete (...) representations are more influenced by conceptual role than continuous representations. We end by arguing that the presence of discrete representations in cognitive systems entails that computationalism (i.e., the view that the mind is a computational device) is true, and that cognitive science should embrace representational pluralism. (shrink)

Analogical reminding in humans and machines is a great source for chance discoveries because analogical reminding can produce representational change and thereby produce insights. Here, we present a new kind of representational change associated with analogical reminding called packing. We derived the algorithm in part from human data we have on packing. Here, we explain packing and its role in analogy making, and then present a computer model of packing in a micro-domain. We conclude that packing is likely used in (...) human chance discoveries, and is needed if our machines are to make their own chance discoveries. (shrink)

The perceptual symbol system view assumes that perceptual representations have a role-argument structure. A role-argument structure is often incorporated into amodal symbol systems in order to explain conceptual functions like abstraction and rule use. The power of perceptual symbol systems to support conceptual functions is likewise rooted in its use of structure. On Barsalou's account, this capacity to use structure (in the form of frames) must be innate.

Pothos suggests dispensing with the distinction between rules and similarity, without defining what is meant by either term. We agree that there are problems with the distinction between rules and similarity, but believe these will be solved only by exploring the representations and processes underlying cases purported to involve rules and similarity.

The proposed model is put forward as a template for the dynamical systems approach to embodied cognition. In order to extend this view to cognitive processing in general, however, two limitations must be overcome. First, it must be demonstrated that sensorimotor coordination of the type evident in the A-not-B error is typical of other aspects of cognition. Second, the explanatory utility of dynamical systems models must be clarified.

In order to develop sophisticated models of the core domains of knowledge that support complex cognitive processing in infants and children, developmental psychologists have mapped out the content of these knowledge domains. This research strategy may provide a blueprint for advancing research on adult cognitive processing. I illustrate this suggestion with examples from analogical reasoning and decision making.

Representation is a central part of models in cognitive science, but recently this idea has come under attack. Researchers advocating perceptual symbol systems, situated action, embodied cognition, and dynamical systems have argued against central assumptions of the classical representational approach to mind. We review the core assumptions of the dominant view of representation and the four suggested alternatives. We argue that representation should remain a core part of cognitive science, but that the insights from these alternative approaches must be incorporated (...) into models of cognitive processing. (shrink)

We argue that the dynamical and computational hypotheses are compatible and in fact need each other: they are about different aspects of cognition. However, only computationalism is about the information-processing aspect. We then argue that any form of information processing relying on matching and comparing, as cognition does, must use discrete representations and computations defined over them.

Tests of economic theory often focus on choice outcomes and find significant individual differences in these outcomes. This variability may mask universal psychological processes that lead to different choices because of differences across cultures in the information people have available when making decisions. On this view, decision making research within and across cultures must focus on the processes underlying choice.

Different aspects of people's interactions with money are best conceptualized using the drug and tool theories. The key question is when these models of money are most likely to guide behavior. We suggest that the Drug Theory characterizes motivationally active uses of money and that the Tool Theory characterizes behavior in motivationally cool situations. (Published Online April 5 2006).

Machery argues that concepts are too heterogeneous to be a natural kind. I argue that the book does not go far enough. Theories of concepts assume that the task of categorizing warrants a unique set of cognitive constructs. Instead, cognitive science must look across tasks to find a fundamental set of cognitive mechanisms.

The representational distortion (RD) approach to similarity (e.g., Hahn, Chater, & Richardson, 2003) proposes that similarity is computed using the transformation distance between two entities. We argue that researchers who adopt this approach need to be concerned with how representational transformations can be determined a priori. We discuss several roadblocks to using this approach. Specifically we demonstrate the difficulties inherent in determining what transformations are psychologically salient and the importance of considering the directionality of transformations.

Relational representation abilities are a crucial cognitive difference between human and nonhuman animals. We argue that relational reasoning and representation supports the development of culture that increases in complexity. Thus, these abilities are a force that magnifies the apparent difference in cognitive abilities between humans and nonhumans.

It is important to take a developmental approach to the problem of analogy. One limitation of this approach, however, is that it does not deal with the complexity of making analogical inferences. There are a few key principles of analogical inference that are not well captured by the analogical relational priming (ARP) model.

There are two roadblocks to using game theory as a unified theory of the behavioral sciences. First, there may not be a single explanatory framework suitable for explaining psychological processing. Second, even if there is such a framework, game theory is too limited, because it focuses selectively on decision making to the exclusion of other crucial cognitive processes. (Published Online April 27 2007).

Pickering & Garrod (P&G) suggest that communicators synchronize their processing at a number of linguistic levels. Whereas their explanation suggests that representations are being compared across individuals, there must be some representation of all conversation participants in each participant's head. At the level of the situation model, it is important to maintain separate representations for each participant. At other levels, it seems less crucial to have a separate representation for each participant. This analysis suggests that different mechanisms may synchronize representations (...) at different linguistic levels. (shrink)

The target article suggests that many practices of experimental economists are preferable to those used by psychologists studying judgment and decision making. The advantages of the psychological approach become clear when the focus of research shifts from choice output to choice processes. I illustrate this point with an example from research on similarity comparisons.

Multidimensional space representations like those posited in Edelman's target article are not sufficient to capture all similarity phenomena. We discuss phenomena that are compatible with models of similarity that assume structured relational representations. An adequate model of similarity and perception will require multiple approaches to representation.