Artificial Intelligence

The dynamical hypothesis in cognitive science is directly opposed to the computational hypothesis that argues cognitive agents are digital computers. According to van Gelder (2003), the dynamical hypothesis is the claim that "cognitive agents are dynamical systems," (1). There are two main elements of the dynamical hypothesis. The first is the nature hypothesis that makes the claim that cognitive agents are dynamical systems. The second is known as the knowledge hypothesis that claims that cognitive agents can be understood dynamically. Brooks maintains that once we impart the ability of being and reacting to computers, higher cognitive skills like solving, language, expert knowledge and application, and reason are possible (Brains 2003). For this to occur the "essence" of being and reacting involved a dynamic environment and the need to react to it, "This essence is the ability to move around in a dynamic environment, sensing the surroundings to a degree sufficient to achieve the necessary maintenance of life and reproduction" (Brains 2003).

In this way it is plausible to think of the mind as a dynamical system because it reacts to the dynamism of environmental stimuli. This is where the computational model falls short of explaining cognition and intelligence to van Gelder, Brooks, and Dreyfus because activity requires knowledge of brain functions that play a causal role in behavior, not just simple observation of correlatio

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comes from Fodor who holds that the mind's computations are operations over symbolic representations according to formal rules. However, for this model to success it requires explicit representation of the rules in contrast to non-symbolic models of computational thought. Like a computer processor operates on the symbols of its language according to a rule, so the mind is though to act on symbols according to rules. Both Fodor and Pylyshyn argue that the computational model of the mind is the only one that can do justice in explaining mental phenomenon. Fodor and Pylyshyn argue that "connectionist models of compositionality must be mere implementations," (Chalmers 2003, 1). Both classicism (computational) and connectionism posit internal mental representations in order to explain cognitive behavior. They are also both aimed at providing cognitive level explanations. Since both posit representations that encode states of the world, they both offer cognitive explanations of the language of thought. However, in classicism's language of thought (LOT) the basic representational relations are causal and constitutive. In other words, perhaps neurons in the brain act like such symbols. In connectionism, there are distributed re

Category: Science - A