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Artificial Life

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  • Mark Bedau, Artificial Life.
    Contemporary artificial life (also known as “ALife”) is an interdisciplinary study of life and life-like processes. Its two most important qualities are that it focuses on the essential rather than the contingent features of living systems and that it attempts to understand living systems by artificially synthesizing extremely simple forms of them. These two qualities are connected. By synthesizing simple systems that are very life-like and yet very unfamiliar, artificial life constructively explores the boundaries of what is possible for life. (...)
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  • Mark Bedau, Artificial Life Illuminates Human Hyper-Creativity.
    The aim of this chapter is to show how the technological research activity called “artificial life” is shedding new light on human creativity. Artificial life aims to understanding the fundamental behavior of life-like systems by synthesizing that behavior in artificial systems (more on artificial life below). One of the most interesting behaviors of living systems is their creativity. Biological creativity can be found in both individual living organisms and in the whole biosphere—the entire interconnected system comprised of all forms of (...)
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  • Mark Bedau, Philosophical Content and Method of Artificial Life.
    The field of artificial life is enriching both the content and method of philosophy. One example of the impact of artificial life on the content of philosophy is the light it sheds on the perennial philosophical question of the nature of emergent pheonomena in general. Another second example is the way it highlights and promises to explain the suppleness of mental processes. Artificial life's computational thought experiments also provide philosophy with a methodological innovation. The limitations of the central arguments in (...)
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  • Mark Bedau, The Scientific and Philosophical Scope of Artificial Life.
    The new interdisciplinary science of artificial life has had a connection with the arts from its inception. This paper provides an overview of artificial life, reviews its key scientific challenges, and discusses its philosophical implications. It ends with a few words about the implications of artificial life for the arts.
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  • Rodney A. Brooks, Artificial Life and Real Robots.
    The first part of this paper explores the general issues in using Artificial Life techniques to program actual mobile robots. In particular it explores the difficulties inherent in transferring programs evolved in a simulated environment to run on an actual robot. It examines the dual evolution of organism morphology and nervous systems in biology. It proposes techniques to capture some of the search space pruning that dual evolution offers in the domain of robot programming. It explores the relationship between robot (...)
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  • David Chalmers (manuscript). The Evolution of Learning: An Experiment in Genetic Connectionism. .
    This paper explores how an evolutionary process can produce systems that learn. A general framework for the evolution of learning is outlined, and is applied to the task of evolving mechanisms suitable for supervised learning in single-layer neural networks. Dynamic properties of a network’s information-processing capacity are encoded genetically, and these properties are subjected to selective pressure based on their success in producing adaptive behavior in diverse environments. As a result of selection and genetic recombination, various successful learning mechanisms evolve, (...)
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  • David J. Chalmers (unknown). How Cartesian Dualism Might Have Been True. .
    We could have been characters in a huge computer simulation. It is a familiar idea that the whole world might be simulated on a computer, and things would seem exactly the same to us (and indeed, who is to say that we are not).
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  • Daniel C. Dennett, Artificial Life as Philosophy.
    There are two likely paths for philosophers to follow in their encounters with Artificial Life: they can see it as a new way of doing philosophy, or simply as a new object worthy of philosophical attention using traditional methods. Is Artificial Life best seen as a new philosophical method or a new phenomenon? There is a case to be made for each alternative, but I urge philosophers to take the leap and consider the first to be the more important and (...)
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  • Daniel C. Dennett (1990). Artificial Life: A Feast for the Imagination. Biology and Philosophy 5 (4).
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  • Claus Emmeche, Life as an Abstract Phenomenon: Is Artificial Life Possible?
    Is life a property of the material structure of a living system or an abstract form of organization that can be realized in other media; artificial as well as natural? One version of the Artificial Life research programme presumes, that one can separate the logical form of an organism from its material basis of construction, and that its capacity to live and reproduce is a property of the form, not the matter (Langton 1989). This seems to oppose the notion of (...)
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  • Claus Emmeche (1991). A Semiotical Reflection on Biology, Living Signs and Artificial Life. Biology and Philosophy 6 (3).
    It is argued, that theory sf signs, especially in the tradition of the great philosopher Charles Sanders Peirce (1839–1914) can inspire the study of central problems in the philosophy of biology. Three such problems are considered: (1) The nature of biology as a science, where a semiotically informed pluralistic approach to the theory of science is introduced. (2) The peculiarity of the general object of biology, where a realistic interpretation of sign- and information-concepts is required to see sign-processes as immanent (...)
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  • Stevan Harnad (1994). Levels of Functional Equivalence in Reverse Bioengineering: The Darwinian Turing Test for Artificial Life. Artificial Life 1 (3):93-301.
    Both Artificial Life and Artificial Mind are branches of what Dennett has called "reverse engineering": Ordinary engineering attempts to build systems to meet certain functional specifications, reverse bioengineering attempts to understand how systems that have already been built by the Blind Watchmaker work. Computational modelling (virtual life) can capture the formal principles of life, perhaps predict and explain it completely, but it can no more be alive than a virtual forest fire can be hot. In itself, a computational model is (...)
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    Export citation  | Other links: eprints.resist.ecs.soton.ac.uk portal.acm.org cogprints.org cogprints.soton.ac.uk mitpress.mit.edu cogsci.soton.ac.uk ecs.soton.ac.uk eprints.ecs.soton.ac.uk cogprints.ecs.soton.ac.uk citebase.eprints.org   | Scholar | More..
  • Stevan Harnad, Artificial Life: Synthetic Versus Virtual.
    Artificial life can take two forms: synthetic and virtual. In principle, the materials and properties of synthetic living systems could differ radically from those of natural living systems yet still resemble them enough to be really alive if they are grounded in the relevant causal interactions with the real world. Virtual (purely computational) "living" systems, in contrast, are just ungrounded symbol systems that are systematically interpretable as if they were alive; in reality they are no more alive than a virtual (...)
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  • Brian L. Keeley (1994). Against the Global Replacement: On the Application of the Philosophy of Artificial Intelligence to Artificial Life. In C.G. Langton (ed.), Artificial Life III: Proceedings of the Workshop on Artificial Life. Reading, Mass: Addison-Wesley.
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  • Sarah Kember (2003). Cyberfeminism and Artificial Life. Routledge.
    Cyberfeminism and Artificial Life examines construction, manipulation and re-definition of life in contemporary technoscientific culture. It takes a critical political view of the concept of life as information, tracing this through the new biology and the changing discipline of artificial life and its manifestation in art, language, literature, commerce and entertainment. From cloning to computer games, and incorporating an analysis of hardware, software and 'wetware', Sarah Kember demonstrates how this relatively marginal field connects with, and connects up global networks of (...)
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  • Marc Lange (1996). Life, "Artificial Life," and Scientific Explanation. Philosophy of Science 63 (2):225-244.
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  • Steven Luper, Natural Resources, Gadgets, and Artificial Life.
    Inventions should belong to no one. It does not matter whether the invention is a genetically engineered life form or a mechanism such as the more familiar radio: it should not be private property. More precisely, types of things invented by people (such as the radio or the dog) as opposed to particular things (such as the radio in my car and the dog in my back yard) should not be private property, with one qualification: At most, people should expect (...)
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  • Pete Mandik, Cognitive Cellular Automata.
    In this paper I explore the question of how artificial life might be used to get a handle on philosophical issues concerning the mind-body problem. I focus on questions concerning what the physical precursors were to the earliest evolved versions of intelligent life. I discuss how cellular automata might constitute an experimental platform for the exploration of such issues, since cellular automata offer a unified framework for the modeling of physical, biological, and psychological processes. I discuss what it would take (...)
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  • Pete Mandik (2003). Varieties of Representation in Evolved and Embodied Neural Networks. Biology and Philosophy 18 (1):95-130.
    In this paper I discuss one of the key issuesin the philosophy of neuroscience:neurosemantics. The project of neurosemanticsinvolves explaining what it means for states ofneurons and neural systems to haverepresentational contents. Neurosemantics thusinvolves issues of common concern between thephilosophy of neuroscience and philosophy ofmind. I discuss a problem that arises foraccounts of representational content that Icall ``the economy problem'': the problem ofshowing that a candidate theory of mentalrepresentation can bear the work requiredwithin in the causal economy of a mind and (...)
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    Export citation  | Other links: citeseer.ist.psu.edu cogs.indiana.edu petemandik.com testweb.wpunj.edu springerlink.com kluweronline.com ingentaconnect.com   | Scholar | More..
  • Pete Mandik (2002). Synthetic Neuroethology. In James Moor & Terrell Ward Bynum (eds.), Cyberphilosophy: The Intersection of Philosophy and Computing. Blackwell Pub..
    Computation and philosophy intersect three times in this essay. Computation is considered as an object, as a method, and as a model used in a certain line of philosophical inquiry concerning the relation of mind to matter. As object, the question considered is whether computation and related notions of mental representation constitute the best ways to conceive of how physical systems give rise to mental properties. As method and model, the computational techniques of artificial life and embodied evolutionary connectionism are (...)
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  • Robert Pennock, Learning Evolution and the Nature of Science Using Evolutionary Computing and Artificial Life.
    Because evolution in natural systems happens so slowly, it is dif- ficult to design inquiry-based labs where students can experiment and observe evolution in the way they can when studying other phenomena. New research in evolutionary computation and artificial life provides a solution to this problem. This paper describes a new A-Life software environment – Avida-ED – in which undergraduate students can test evolutionary hypotheses directly using digital organisms that evolve on their own through the very mechanisms that Darwin discovered.
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  • Michael Ruse (1999). Margaret A. Boden, Ed., the Philosophy of Artificial Life, Oxford Readings in Philosophy, New York: Oxford University Press, 1996, VIII + 405 Pp., 65.00 (Cloth), ISBN 0-19-875154-0;65.00 (Cloth), ISBN 0-19-875154-0; 19.95 (Paper), ISBN 0-19-875155-. Minds and Machines 9 (1).
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  • Cosma Shalizi, Artificial Life.
    We have created the homunculus and have seen the monstrous being. Forty days the sperm lay buried in manure and each day at noon the Master turned his magnet across it, muttering foreign words. Then, on the fortieth day he showed me the resemblance of a man, but it was transparent, without a corpus. He told me we should feed the loathsome object for exactly forty weeks, and all this time allow it to lie in its bed of manure in (...)
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  • Porfirio Silva & Pedro U. Lima (2007). Institutional Robotics. In F. Almeida e Costa et al (ed.), Advances in Artificial Life. ECAL 2007. Springer-Verlag.
    Pioneer approaches to Artificial Intelligence have traditionally neglected, in a chronological sequence, the agent body, the world where the agent is situated, and the other agents. With the advent of Collective Robotics approaches, important progresses were made toward embodying and situating the agents, together with the introduction of collective intelligence. However, the currently used models of social environments are still rather poor, jeopardizing the attempts of developing truly intelligent robot teams. In this paper, we propose a roadmap for a new (...)
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  • John P. Sullins (2005). Ethics and Artificial Life: From Modeling to Moral Agents. Ethics and Information Technology 7 (3).
    Artificial Life (ALife) has two goals. One attempts to describe fundamental qualities of living systems through agent based computer models. And the second studies whether or not we can artificially create living things in computational mediums that can be realized either, virtually in software, or through biotechnology. The study of ALife has recently branched into two further subdivisions, one is “dry” ALife, which is the study of living systems “in silico” through the use of computer simulations, and the other is (...)
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  • Liz Stillwaggon Swan (2009). Synthesizing Insight: Artificial Life as Thought Experimentation in Biology. Biology and Philosophy 24 (5).
    What is artificial life? Much has been said about this interesting collection of efforts to artificially simulate and synthesize lifelike behavior and processes, yet we are far from having a robust philosophical understanding of just what Alifers are doing and why it ought to interest philosophers of science, and philosophers of biology in particular. In this paper, I first provide three introductory examples from the particular subset of artificial life I focus on, known as ‘soft Alife’ (s-Alife), and follow up (...)
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  • Alex Vereschagin, Mike Collins & Pete Mandik (2007). Evolving Artificial Minds and Brains. In Drew Khlentzos & Andrea Schalley (eds.), Mental States Volume 1: Evolution, function, nature. John Benjamins.
    We explicate representational content by addressing how representations that ex- plain intelligent behavior might be acquired through processes of Darwinian evo- lution. We present the results of computer simulations of evolved neural network controllers and discuss the similarity of the simulations to real-world examples of neural network control of animal behavior. We argue that focusing on the simplest cases of evolved intelligent behavior, in both simulated and real organisms, reveals that evolved representations must carry information about the creature’s environ- ments (...)
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