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Switch to: References
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Many previous treatments of voluntary behavior have viewed intentions as causes of behavior. This has resulted in several dilemmas, including a dilemma concerning the origin of intentions. The present article circumvents traditional dilemmas by treating intentions as constraints that restrict degrees of freedom for behavior. Constraints self-organize as temporary dynamic structures that span the mind-body divide. This treatment of intentions and voluntary behavior yields a theory of intentionality that is consistent with existing findings and supported by current research. |
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How do people decide what to say in context? Many theories of pragmatics assume that people have specialized knowledge that drives them to utter certain words in different situations. But these theories are mostly unable to explain both the regularity and variability in people’s speech behaviors. Our purpose in this article is to advance a view of pragmatics based on complexity theory, which specifically explains the pragmatic choices speakers make in conversations. The concept of self-organized criticality sheds light on how (...) |
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The literature on coordination within and between individuals is reviewed, with an emphasis on the inherent transience of coordination patterns in behavioral activity. This transience is integral to understanding cognitive activity as flexible patterns of coordination in brain, body, and environment. Kello reviews the articles in this special issue as contributions to understanding the role of context in shaping or interpreting coordination patterns in human behavior. |
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Long‐range correlation is a general class of coordination pattern found to be common to the intrinsic dynamics of complex systems, including human behavior. Balasubramaniam, Hove, and Médé investigate intrinsic dynamics in repeated finger movements, and they find that different measures of movement dynamics yield different long‐range correlations. Results shed light on the way that coordination patterns are expressed as a function of measurement context. |
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The finding of fractal scaling (FS) in behavioral sequences has raised a debate on whether FS is a pervasive property of the cognitive system or is the result of specific processes. Inferences about the origins of properties in time sequences are causal. That is, as opposed to correlational inferences reflecting instantaneous symmetrical relations, causal inferences concern asymmetric relations lagged in time. Here, I integrate Granger‐causality with inferences about FS. Four simulations illustrate that causal analyses can isolate distinct FS sources, whereas (...) |
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The finding of fractal scaling (FS) in behavioral sequences has raised a debate on whether FS is a pervasive property of the cognitive system or is the result of specific processes. Inferences about the origins of properties in time sequences are causal. That is, as opposed to correlational inferences reflecting instantaneous symmetrical relations, causal inferences concern asymmetric relations lagged in time. Here, I integrate Granger-causality with inferences about FS. Four simulations illustrate that causal analyses can isolate distinct FS sources, whereas (...) |
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Recent literature concerning laws of nature highlight the close relationship between general metaphysics and philosophy of science. In particular, a person's theoretical commitments in either have direct implications for her stance on laws. In this dissertation, I argue that an ontic structural realist should be a realist about laws, but only within a non-Whiteheadean process framework. Without the adoption of a process framework, any account of laws the ontic structural realist offers will require metaphysical commitments that are at odds with (...) |
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Many psychological studies have shown that human‐generated sequences are hardly ever random in the strict mathematical sense. However, what remains an open question is the degree to which this (in)ability varies between people and is affected by contextual factors. Herein, we investigated this problem. In two studies, we used a modern, robust measure of randomness based on algorithmic information theory to assess human‐generated series. In Study 1 (), in a factorial design with task description as a between‐subjects variable, we tested (...) |
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