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Phase transitions, similar to those seen in physical systems, are observed in spreading activation networks. Such networks are used both in theories of cognition and in artificial intelligence applications. This result confirms a predicted abrupt behavioral change as either the topology of the network or the activation parameters are varied across phase(More)
Much of the work on execution assumes that the agent constantly senses the environment, which lets it respond immediately to errors or unexpected events. In this paper , we argue that this purely reactive strategy is only optimal if sensing is inexpensive, and we formulate a simple model of execution that incorporates the cost of sensing. We present an(More)
Numerous human learning phenomena have been observed and captured by individual laws, but no unified theory of learning has succeeded in accounting for these observations. A theory and model are proposed that account for two of these phenomena: the power law of practice and the problem-solving fan-effect. The power law of practice states that the speed of(More)
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