Abducing chances in hybrid humans as decision makers
Information Sciences: an International Journal
Beyond Mind: How Brains Make up Artificial Cognitive Systems
Minds and Machines
Faking chance cognitive niche impoverishment
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part III
From epistemic luck to chance-seeking: the role of cognitive niche construction
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
Perverting Activism: Cyberactivism and Its Potential Failures In Enhancing Democratic Institutions
International Journal of Technoethics
International Journal of Technoethics
Facebook Has It: The Irresistible Violence of Social Cognition in the Age of Social Networking
International Journal of Technoethics
Proceedings of the Virtual Reality International Conference: Laval Virtual
Ethics and Information Technology
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This volume explores abductive cognition, an important but, at least until the third quarter of the last century, neglected topic in cognition. The book aims at increasing knowledge about creative and expert inferences. The study of these high-levelmethods of abductive reasoning is situated at the crossroads of philosophy, logic, epistemology, artificial intelligence, neuroscience, cognitive psychology, animal cognition and evolutionary theories; that is, at the heart of cognitive science. Philosophers of science in the twentieth century have traditionally distinguished between the inferential processes active in the logic of discovery and the ones active in the logic of justification. Most have concluded that no logic of creative processes exists and, moreover, that a rational model of discovery is impossible. In short, scientific creative inferences are irrational and there is no reasoning to hypotheses. On the other hand, some research in the area of artificial intelligence has shown that methods for discovery could be found that are computationally adequate for rediscovering or discovering for the first time empirical or theoretical laws and theorems.