In this investigation of the psychological relationship between shape and time, Leyton argues compellingly that shape is used by the mind to recover the past and as such it forms a basis for memory. Michael Leyton's arguments about the nature of perception and cognition are fascinating, exciting, and sure to be controversial. In this investigation of the psychological relationship between shape and time, Leyton argues compellingly that shape is used by the mind to recover the past and as such it forms a basis for memory. He elaborates a system of rules by which the conversion to memory takes place and presents a number of detailed case studies--in perception, linguistics, art, and even political subjugation--that support these rules. Leyton observes that the mind assigns to any shape a causal history explaining how the shape was formed. We cannot help but perceive a deformed can as a dented can. Moreover, by reducing the study of shape to the study of symmetry, he shows that symmetry is crucial to our everyday cognitive processing. Symmetry is the means by which shape is converted into memory. Perception is usually regarded as the recovery of the spatial layout of the environment. Leyton, however, shows that perception is fundamentally the extraction of time from shape. In doing so, he is able to reduce the several areas of computational vision purely to symmetry principles. Examining grammar in linguistics, he argues that a sentence is psychologically represented as a piece of causal history, an archeological relic disinterred by the listener so that the sentence reveals the past. Again through a detailed analysis of art he shows that what the viewer takes to be the experience of a painting is in fact the extraction of time from the shapes of the painting. Finally he highlights crucial aspects of the mind's attempt to recover time in examples of political subjugation.

Which causal patterns are involved in mental processes?On what mechanisms does the self-organisation of cognitive structure rest? Can a naturalistic view account for the basic resources of intentionality, while avoiding the objections to reductive materialism? By considering the developmental, phenomenological and biological aspects linking mind and causality, this volume offers a state-of-the art theoretical proposal emphasising the fine-tuning of cognition with the complexity of bodily dynamics.In contrast to the de-coupling of mind from the physical environment in classical information-processing models, growth of brain’s architecture and stabilisation of perception­–action cycles are considered decisive, with no need for an eliminative approach to representations pursued by neural network models. The tools provided by physics and biology for the description of massive causal interactions, on top of which ‘qualitative’ changes occur, are exploited to suggest a model of the mind as a many-layered, co-evolving system. (Series A)

William Child examines two central ideas in the philosophy of mind, and argues that (contrary to what many philosophers have thought) an understanding of the mind can and should include both. These are causalism, the idea that causality plays an essential role in our understanding of the mental; and interpretationism, the idea that we can gain an understanding of belief and desire by considering the ascription of attitudes to people on the basis of what they say and do.

This text presents 17 of Nicholas Jolley's essays on early modern philosophy. They focus on two main themes: the debate over the nature of causality; and the issues posed by Descartes' innovations in the philosophy of mind. Together, they show that philosophers in the period are systematic critics of their contemporaries and predecessors.

This title provides an introduction to assumptions, algorithms, and techniques of causal Bayes nets and graphical causal models in the context of psychological examples. It demonstrates their potential as a powerful tool for guiding experimental inquiry.

One philosophical approach to causation sees counterfactual dependence as the key to the explanation of causal facts: for example, events c (the cause) and e (the effect) both occur, but had c not occurred, e would not have occurred either. The counterfactual analysis of causation became a focus of philosophical debate after the 1973 publication of the late David Lewis's groundbreaking paper, "Causation," which argues against the previously accepted "regularity" analysis and in favor of what he called the "promising alternative" of the counterfactual analysis. Thirty years after Lewis's paper, this book brings together some of the most important recent work connecting—or, in some cases, disputing the connection between—counterfactuals and causation, including the complete version of Lewis's Whitehead lectures, "Causation as Influence," a major reworking of his original paper. Also included is a more recent essay by Lewis, "Void and Object," on causation by omission. Several of the essays first appeared in a special issue of the Journal of Philosophy, but most, including the unabridged version of "Causation as Influence," are published for the first time or in updated forms. Other topics considered include the "trumping" of one event over another in determining causation; de facto dependence; challenges to the transitivity of causation; the possibility that entities other than events are the fundamental causal relata; the distinction between dependence and production in accounts of causation; the distinction between causation and causal explanation; the context-dependence of causation; probabilistic analyses of causation; and a singularist theory of causation.

A renowned philosopher argues that singular causation in the mind is not grounded in general patterns of causation, a claim on behalf of human distinctiveness, which has implications for the future of social robots. A blab droid is a robot with a body shaped like a pizza box, a pair of treads, and a smiley face. Guided by an onboard video camera, it roams hotel lobbies and conference centers, asking questions in the voice of a seven-year-old. “Can you help me?” “What is the worst thing you’ve ever done?” “Who in the world do you love most?” People pour their hearts out in response. This droid prompts the question of what we can hope from social robots. Might they provide humanlike friendship? Philosopher John Campbell doesn’t think so. He argues that, while a social robot can remember the details of a person’s history better than some spouses can, it cannot empathize with the human mind, because it lacks the faculty for thinking in terms of singular causation. Causation in Psychology makes the case that singular causation is essential and unique to the human species. From the point of view of practical action, knowledge of what generally causes what is often all one needs. But humans are capable of more. We have a capacity to imagine singular causation. Unlike robots and nonhuman animals, we don’t have to rely on axioms about pain to know how ongoing suffering is affecting someone’s ability to make decisions, for example, and this knowledge is not a derivative of general rules. The capacity to imagine singular causation, Campbell contends, is a core element of human freedom and of the ability to empathize with human thoughts and feelings.