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)

A recently developed model of general collective intelligence defines a method for organizing humans or artificially intelligent agents that is believed to create the potential to exponentially increase the general problem-solving ability of groups of such entities over that of any individual entity. An analysis based on this model suggests that many and perhaps all “wicked problems” are collective optimization problems that cannot reliably be addressed without a system of collective optimization, but that might be reliably addressed through such a (...) system. This paper briefly introduces the concept of GCI as well as why it is a system of collective optimization, and explores why “wicked problems” from the perspective of GCI are collective optimization problems, and therefore why such problems might require GCI to be reliably solvable. (shrink)

Turing's analysis of computation is a fundamental part of the background of cognitive science. In this paper it is argued that a re‐interpretation of Turing's work is required to underpin theorizing about cognitive architecture. It is claimed that the symbol systems view of the mind, which is the conventional way of understanding how Turing's work impacts on cognitive science, is deeply flawed. There is an alternative interpretation that is more faithful to Turing's original insights, avoids the criticisms made of the (...) symbol systems approach and is compatible with the growing interest in agent‐environment interaction. It is argued that this interpretation should form the basis for theories of cognitive architecture. (shrink)

A recently developed model of general collective intelligence defines a method for organizing humans or artificially intelligent agents that is believed to create the potential to exponentially increase the general problem-solving ability of groups of such entities over that of any individual entity. An analysis based on this model suggests that many and perhaps all “wicked problems” are collective optimization problems that cannot reliably be addressed without a system of collective optimization, but that might be reliably addressed through such a (...) system. This paper briefly introduces the concept of GCI as well as why it is a system of collective optimization, and explores why “wicked problems” from the perspective of GCI are collective optimization problems, and therefore why such problems might require GCI to be reliably solvable. (shrink)