There is a long tradition in formal epistemology and in the psychology of reasoning to investigate indicative conditionals. In psychology, the propositional calculus was taken for granted to be the normative standard of reference. Experimental tasks, evaluation of the participants’ responses and psychological model building, were inspired by the semantics of the material conditional. Recent empirical work on indicative conditionals focuses on uncertainty. Consequently, the normative standard of reference has changed. I argue why neither logic nor standard probability theory provide (...) appropriate rationality norms for uncertain conditionals. I advocate coherence based probability logic as an appropriate framework for investigating uncertain conditionals. Detailed proofs of the probabilistic non-informativeness of a paradox of the material conditional illustrate the approach from a formal point of view. I survey selected data on human reasoning about uncertain conditionals which additionally support the plausibility of the approach from an empirical point of view. (shrink)

According to Frankfurt’s analysis, bullshitting and lying necessarily differ in intention. I argue contra Frankfurt that (i) bullshitting can be lying, and that (ii) bullshitting need involve neither misrepresentation nor intention to deceive. My discussion suggests that bullshit is not capturable by a simple formula and that, although illuminating, Frankfurt’s analysis is limited to one paradigm.

A review of Geoffrey Marnell, Mathematical Doodlings: Curiosities, conjectures, and challenges.

This is a note and query concerning Scott Gardiner’s novel, The Dominion of Wyley McFadden (Random House Canada, 2000). I raise a question about the attitude of the main character toward the newest fertility technologies.

A large body of compelling evidence has been accumulated demonstrating that embodiment – the agent’s physical setup, including its shape, materials, sensors and actuators – is constitutive for any form of cognition and as a consequence, models of cognition need to be embodied. In contrast to methods from empirical sciences to study cognition, robots can be freely manipulated and virtually all key variables of their embodiment and control programs can be systematically varied. As such, they provide an extremely powerful tool (...) of investigation. We present a robotic bottom-up or developmental approach, focusing on three stages: (a) low-level behaviors like walking and reflexes, (b) learning regularities in sensorimotor spaces, and (c) human-like cognition. We also show that robotic based research is not only a productive path to deepening our understanding of cognition, but that robots can strongly benefit from human-like cognition in order to become more autonomous, robust, resilient, and safe. (shrink)

Morphological Computation is based on the observation that biological systems seem to carry out relevant computations with their morphology (physical body) in order to successfully interact with their environments. This can be observed in a whole range of systems and at many different scales. It has been studied in animals – e.g., while running, the functionality of coping with impact and slight unevenness in the ground is "delivered" by the shape of the legs and the damped elasticity of the muscle-tendon (...) system – and plants, but it has also been observed at the cellular and even at the molecular level – as seen, for example, in spontaneous self-assembly. The concept of morphological computation has served as an inspirational resource to build bio-inspired robots, design novel approaches for support systems in health care, implement computation with natural systems, but also in art and architecture. As a consequence, the field is highly interdisciplinary, which is also nicely reflected in the wide range of authors that are featured in this e-book. We have contributions from robotics, mechanical engineering, health, architecture, biology, philosophy, and others. (shrink)

Luck has become an increasingly important factor in epistemology during recent years as either a preventor of knowledge (Pritchard 2013) or even as one of the conditions of knowledge (Zagzebski 1994, Hetherington 2013), thus begging the question of its definition. Following the probabilistic and degree-minding "new paradigm psychology of reasoning" (Evans 2012, Elqayam & Over 2012, Pfeifer & Douven 2014) and renouncing the "old paradigm" of bivalence, the first main feature of this article lies in the introduction of "gradualism" (...) according to which vast parts of reality comes in degrees (=metaphysical or ontological gradualism) and, given that theoretical constructs are supposed to accurately correspond to reality, according to which gradualistic or degree-minding frameworks need to be established in all of philosophy or science (=theoretical gradualism). As the second and more central feature of this article, and building on gradualism and Riggs' (2007) pivotal idea that "luck comes in degrees", I will then develop my own gradualistic account of luck with two always necessary gradual conditions (low enough chance and high enough significance) and one sometimes necessary gradual condition (low enough control or high enough lack of control). During the presentation of this new account of luck, I will also deliver decisive arguments against prominent luck philosopher Duncan Pritchard's latest version of the modal account of luck (forthcoming) which contains major mistakes in respect to all three conditions of luck. (shrink)