Philosophy and Theory of Artificial Intelligence (Studies in Applied Philosophy, Epistemology and Rational Ethics)
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Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science.
We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here.
Artificial Intelligence, SAPERE 5, pp. 43–58. c Springer-Verlag Berlin Heidelberg 2013 springerlink.com 44 D. Davenport following paragraphs, I present my own attempt to understand and bring some semblance of order to the topic. I approach the problem as an engineering task and begin by analysing the diﬀerence between the classical symbolic & connectionist paradigms. Consideration of the functional requirements for cognition, including the environmental/evolutionary contexts in which agents
programs or structures that seem to refer to nothing whatsoever. Take this piece of Pascal code: program do_nothing; begin end. It is a correct specification of a program that does nothing. Similarly, a connectionist network with two interconnected nodes such that either node gets activated whenever the other one is seems to do some computation, albeit a trivial one. What is the referent, again? This is why I suggest, like Fresco (2010) and Piccinini (2006), that it is not a good idea to wait
states in order to follow traits (indications of ’forces’, that is, singularities or self-ordering capacities) in material to reveal their virtual structures or multiplicities.  The difference between minor science and Royal science, Refers only to a differential in the rhythm and scope of the actual-virtual system From our own historically specific point of view, some terms and concepts will necessarily appear more adequate to the task than others. Science does not describe an objective state
Semantic Web technologies. All in all this clearly has contributed to making SubTuring I and SubTuring II the challenges within the overall SubTuring framework which are closest to be resolved (although there still is quite some work left to be done). 4.2 SubTuring III: Change of Paradigm The human rationality task formulated in SubTuring III, in one form or another is up to a certain extent part of the research questions asked in (amongst others) artificial general intelligence, cognitive
translations). I think this is an important part of the quote, so it's good to go back to the original text: Aristotle uses the word "προαισθανόμενον" – proaisthanomenon this means literally: pro = before, aisthanomenon = perceiving, apprehending, understanding, learning (any of these meanings in this order of frequency) in my view it is clearly a word that is attributed to intelligent, living agents....i.e. ones with cognitive abilities (!)”, . It is difficult to see the modern reading of a