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  1. Tara H. Abraham (2006). Cybernetics and Theoretical Approaches in 20th Century Brain and Behavior Sciences. Biological Theory 1 (4):418-422.
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  2. Pascal Acot, Sandrine Charles & Marie-Laure Delignette-Muller (2000). Artificial Intelligence and Meaning — Some Philosophical Aspects of Decision-Making. Acta Biotheoretica 48 (3-4):173-179.
  3. Alison Adam (2002). Gender/Body/Machine. Ratio 15 (4):354–375.
    This article considers the question of embodiment in relation to gender and whether there are models of artificial intelligence (AI) which can enrol a concept of gender in their design. A central concern for feminist epistemology is the role of the body in the making of knowledge. I consider how this may inform a critique of the AI project and the related area of artificial life (A-Life), the latter area being of most interest in this paper. I explore briefly the (...)
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  4. Almeida E. CostaF (ed.) (2007). Advances in Artificial Life. ECAL 2007. Springer Verlag.
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  5. Robin Attfield (2012). Biocentrism and Artificial Life. Environmental Values 21 (1):83 - 94.
    Biocentrism maintains that all living creatures have moral standing, but need not claim that all have equal moral significance. This moral standing extends to organisms generated through human interventions, whether by conventional breeding, genetic engineering, or synthetic biology. Our responsibilities with regard to future generations seem relevant to non-human species as well as future human generations and their quality of life. Likewise the Precautionary Principle appears to raise objections to the generation of serious or irreversible changes to the quality of (...)
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  6. Simon Bacon (2013). “We Can Rebuild Him!”: The Essentialisation of the Human/Cyborg Interface in the Twenty-First Century, or Whatever Happened to The Six Million Dollar Man? [REVIEW] AI and Society 28 (3):267-276.
    This paper aims to show how recent cinematic representations reveal a far more pessimistic and essentialised vision of Human/Cyborg hybridity in comparison with the more enunciative and optimistic ones seen at the end of the twentieth century. Donna Haraway’s still influential 1985 essay “A Cyborg Manifesto” saw the combination of the organic and the technological as offering new and exciting ways beyond the normalised culturally constructed categories of gender and identity formation. However, more recently critics see her later writings as (...)
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  7. Alexey Bakhirev, MODELS AND LOGIC OF SUBJECTIVE REALITY. SUBJECTIVE WORLDS.
  8. Philip Ball (2011). Unnatural: The Heretical Idea of Making People. Bodley Head.
    From the legendary inventor Daedalus to Goethe's tragic Faust, from the automata-making magicians of E.T.A Hoffmann to Mary Shelley's Victor Frankenstein – ...
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  9. Gary Banham, Artificial Life and the Inhuman Condition.
    Paper published on author's website available at http://www.garybanham.net/PAPERS_files/Artificial%20Life%20and%20the%20Inhuman%20Condition.pdf.
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  10. Gary Banham (2001). Transcendental Philosophy and Artificial Life. CultureMachine 3.
  11. 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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  12. Mark Bedau, 1 Arti Cial Life's Working Hypothesis.
    Arti cial life studies computer models of the processes characteristic of complex adaptive systems|processes like self-organization, self-reproduction, adaptation, and evolution. Complex adaptive systems take many forms, each of which di ers from the others in myriad ways. By abstracting away from the diverse details, arti cial life hopes to reveal fundamental principles governing broad classes of complex adaptive systems. This hope rests on arti cial life's working hypoth-.
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  13. 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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  14. Mark Bedau, Open Problems in Artificial Life Mark A. Bedau∗,†.
    artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated.
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  15. Mark Bedau (2003). Artificial Life. In Luciano Floridi (ed.), Blackwell Guide to the Philosophy of Computing and Information. Blackwell. pp. 505-512.
    Artificial life (also known as “ALife”) is a broad, interdisciplinary endeavor that studies life and life-like processes through simulation and synthesis. The goals of this activity include modelling and even creating life and life-like systems, as well as developing practical applications using intuitions and methods taken from living systems. Artificial life both illuminates traditional philosophical questions and raises new philosophical questions. Since both artificial life and philosophy investigate the essential nature of certain fundamental aspects of reality like life and adaptation, (...)
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  16. Mark A. Bedau, Three Illustrations of Artificial Life's Working Hypothesis.
    Artificial life uses computer models to study the essential nature of the characteristic processes of complex adaptive systems proceses such as self-organization, adaptation, and evolution. Work in the field is guided by the working hypothesis that simple computer models can capture the essential nature of these processes. This hypothesis is illustrated by recent results with a simple population of computational agents whose sensorimotor functionality undergo open-ended adaptive evolution. These might illuminate three aspects of complex adaptive systems in general: punctuated equilibrium (...)
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  17. Mark A. Bedau (1998). Philosophical Content and Method of Artificial Life. In T. W. Bynum & J. Moor (eds.), The Digital Phoenix. Cambridge: Blackwell. pp. 135--152.
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  18. Mark A. Bedau, Richard Crandall & Michael J. Raven (2009). Cryptographic Hash Functions Based on ALife. PSIpress.
    There is a long history of cryptographic hash functions, i.e. functions mapping variable-length strings to fixed-length strings, and such functions are also expected to enjoy certain security properties. Hash functions can be effected via modular arithmetic, permutation-based schemes, chaotic mixing, and so on. Herein we introduce the notion of an artificial-life (ALife) hash function (ALHF), whereby the requisite mixing action of a good hash function is accomplished via ALife rules that give rise to complex evolution of a given system. Various (...)
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  19. Hugues Bersini (2009). How Artificial Life Relates to Theoretical Biology. In Maryvonne Gérin & Marie-Christine Maurel (eds.), Origins of Life: Self-Organization and/or Biological Evolution? Edp Sciences. pp. 61--78.
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  20. Adam Bleckert & Rachel Ol Wong (2011). Identifying Roles for Neurotransmission in Circuit Assembly: Insights Gained From Multiple Model Systems and Experimental Approaches. Bioessays 33 (1):61-72.
  21. A. Boden Margaret (ed.) (1996). The Philosophy of Artificial Life. Oxford University Press.
    This new volume in the acclaimed Oxford Readings in Philosophy sereis offers a selection of the most important philosophical work being done in the new and fast-growing interdisciplinary area of artificial life. Artificial life research seeks to synthesize the characteristics of life by artificial means, particularly employing computer technology. The essays here explore such fascinating themes as the nature of life, the relation between life and mind, and the limits of technology.
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  22. M. A. Boden (1996). The Intellectual Context of Artificial Life. In Margaret A. Boden (ed.), The Philosophy of Artificial Life. Oxford University Press. pp. 1--35.
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  23. Margaret A. Boden (2009). Life and Mind. Minds and Machines 19 (4):453-463.
    It’s sometimes said, and even more often assumed, that life is necessary for mind. If so, and if A-Life promises to throw light on the nature of life as such, then A-Life is in principle highly relevant to the philosophy of mind and cognitive science. However, very few philosophers have attempted to argue for the relation between life and mind. It’s usually taken for granted. Even those (mostly in the Continental tradition, including some with a following in A-Life) who have (...)
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  24. Eric Bonabeau & Paul Bourgine (1994). Artificial Life as It Could Be. World Futures 40 (4):227-249.
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  25. Lashon Booker, Stephanie Forrest, Melanie Mitchell & Rick Riolo (eds.) (2004). Perspectives on Adaptation in Natural and Artificial Systems: Proceedings Volume in the Santa Fe Institute Studies in the Sciences of Complexity. Oxford University Press USA.
    This book is a collection of essays exploring adaptive systems from many perspectives, ranging from computational applications to models of adaptation in living and social systems. The essays on computation discuss history, theory, applications, and possible threats of adaptive and evolving computations systems. The modeling chapters cover topics such as evolution in microbial populations, the evolution of cooperation, and how ideas about evolution relate to economics. The title Perspectives on Adaptation in Natural and Artificial Systems honors John Holland, whose 1975 (...)
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  26. Sarah W. Bottjer (1997). Building a Bird Brain: Sculpting Neural Circuits for a Learned Behavior. Bioessays 19 (12):1109-1116.
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  27. Oliver Bown & Jon McCormack, Creative Agency: A Clearer Goal for Artificial Life in the Arts.
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  28. Rodney Brooks (2001). The Relationship Between Matter and Life. Nature 409 (6818):409-411.
    Researchers in artificial intelligence (AI) Moore’s law states that computational complexity of the models is still far below that and artificial life (Alife) are interested resources for a fixed price roughly double of any living system. New experiments in evo- in understanding the properties of liv- every 18 months. From about 1975 into the lution simulate spatially isolated populations ing organisms so that they can build artificial early 1990s all the gains of Moore’s law went to investigate speciation. Over the (...)
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  29. 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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  30. Angelo Cangelosi & Domenico Parisi (1998). Concepts in Artificial Organisms. Behavioral and Brain Sciences 21 (1):68-69.
    Simulations with neural networks living in a virtual environment can be used to explore and test hypotheses concerning concepts and language. The advantages that result from this approach include (1) the notion that a concept can be precisely defined and examined, (2) that concepts can be studied in both nonverbal and verbal artificial organisms, and (3) concepts have properties that depend on the environment as well as on the organism's adaptive behavior in response to the environment.
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  31. David Chalmers (1992). The Evolution of Learning: An Experiment in Genetic Connectionism. In Connectionist Models: Proceedings of the 1990 Summer School Workshop. Morgan Kaufmann.
    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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  32. David J. Chalmers, 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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  33. Carolina Chang (2001). Biorobotics Researcher: To Be or Not to Be? Behavioral and Brain Sciences 24 (6):1054-1054.
    Much confusion exists within the robotics and the biology communities regarding the definition of biorobotics and the aims and strategies that characterize this approach. Not even the basic criteria for identifying biorobotic research are being applied consistently. Barbara Webb has taken a crucial step towards setting a common ground from which biorobotic systems can be described, analyzed, and compared.
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  34. David F. Channell (1991). The Vital Machine: A Study of Technology and Organic Life. Oxford University Press.
    In 1738, Jacques Vaucanson unveiled his masterpiece before the court of Louis XV: a gilded copper duck that ate, drank, quacked, flapped its wings, splashed about, and, most astonishing of all, digested its food and excreted the remains. The imitation of life by technology fascinated Vaucanson's contemporaries. Today our technology is more powerful, but our fascination is tempered with apprehension. Artificial intelligence and genetic engineering, to name just two areas, raise profoundly disturbing ethical issues that undermine our most fundamental beliefs (...)
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  35. William Clancey (1995). How Situated Cognition is Different From Situated Robotics. In Luc Steels & Rodney Brooks (eds.), The "Artificial Life" Route to "Artificial Intelligence": Building Situated Embodied Agents. Hillsdale, Nj: Lawrence Erlbaum Associates. pp. 227-236.
  36. D. Cliff (1990). Computational Neuroethology: A Provisional Manifesto. In Jean-Arcady Meyer & Stewart W. Wilson (eds.), From Animals to Animats: Proceedings of the First International Conference on Simulation of Adaptive Behavior (Complex Adaptive Systems). Cambridge University Press.
  37. Mark Coeckelbergh (2010). Robot Rights? Towards a Social-Relational Justification of Moral Consideration. Ethics and Information Technology 12 (3):209-221.
    Should we grant rights to artificially intelligent robots? Most current and near-future robots do not meet the hard criteria set by deontological and utilitarian theory. Virtue ethics can avoid this problem with its indirect approach. However, both direct and indirect arguments for moral consideration rest on ontological features of entities, an approach which incurs several problems. In response to these difficulties, this paper taps into a different conceptual resource in order to be able to grant some degree of moral consideration (...)
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  38. Mark Coeckelbergh (2009). Virtual Moral Agency, Virtual Moral Responsibility: On the Moral Significance of the Appearance, Perception, and Performance of Artificial Agents. [REVIEW] AI and Society 24 (2):181-189.
  39. Jack Copeland (ed.) (2004). The Essential Turing: Seminal Writings in Computing, Logic, Philosophy, Artificial Intelligence, and Artificial Life: Plus the Secrets of Enigma. Oxford University Press.
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  40. Roberto Cordeschi (2002). The Discovery of the Artificial: Behavior, Mind and Machines Before and Beyond Cybernetics. Kluwer Academic Publishers.
    Since the second half of the XXth century, researchers in cybernetics and AI, neural nets and connectionism, Artificial Life and new robotics have endeavoured to build different machines that could simulate functions of living organisms, such as adaptation and development, problem solving and learning. In this book these research programs are discussed, particularly as regard the epistemological issues of the behaviour modelling. One of the main novelty of this book consists of the fact that certain projects involving the building of (...)
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  41. Athel Cornish-Bowden, Gabriel Piedrafita, Federico Morán, María Luz Cárdenas & Francisco Montero (2013). Simulating a Model of Metabolic Closure. Biological Theory 8 (4):383-390.
    The goal of synthetic biology is to create artificial organisms. To achieve this it is essential to understand what life is. Metabolism-replacement systems, or (M, R)-systems, constitute a theory of life developed by Robert Rosen, characterized in the statement that organisms are closed to efficient causation, which means that they must themselves produce all the catalysts they need. This theory overlaps in part with other current theories, including autopoiesis, the chemoton, and autocatalytic sets, all of them invoking some idea of (...)
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  42. Luís Parreira Correia (2010). From Natural to Artificial Life. Revista Portuguesa de Filosofia 66 (4):789-802.
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  43. Lindley Darden (1982). Artificial Intelligence and Philosophy of Science: Reasoning by Analogy in Theory Construction. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1982:147 - 165.
    This paper examines the hypothesis that analogies may play a role in the generation of new ideas that are built into new explanatory theories. Methods of theory construction by analogy, by failed analogy, and by modular components from several analogies are discussed. Two different analyses of analogy are contrasted: direct mapping (Mary Hesse) and shared abstraction (Michael Genesereth). The structure of Charles Darwin's theory of natural selection shows various analogical relations. Finally, an "abstraction for selection theories" is shown to be (...)
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  44. Edoardo Datteri (2009). Simulation Experiments in Bionics: A Regulative Methodological Perspective. Biology and Philosophy 24 (3):301-324.
    Bionic technologies connecting biological nervous systems to computer or robotic devices for therapeutic purposes have been recently claimed to provide novel experimental tools for the investigation of biological mechanisms. This claim is examined here by means of a methodological analysis of bionics-supported experimental inquiries on adaptive sensory-motor behaviours. Two broad classes of bionic systems (regarded here as hybrid simulations of the target biological system) are identified, which differ from each other according to whether a component of the biological target system (...)
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  45. Edward Dawidowicz, Vairzora Jackson, Thomas E. Bryant & Martin Adams, The Right Information… and Intelligent Nodes.
    The architecture and mechanism of Intelligent Nodes allows both the Network-centric and Warfighter-centric paradigms to merge. This paper describes a multidisciplinary methodology for developing intelligent software assistants. Such assistants will continue to evolve during the training, exercises and combat, to learn the informational needs of the individual warfighter and combat groups. This symbiotic aggregate of man and computer we call Intelligent Nodes.
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  46. Manuel de Pinedo-Garcia & Jason Noble (2008). Beyond Persons: Extending the Personal/Subpersonal Distinction to Non-Rational Animals and Artificial Agents. Biology and Philosophy 23 (1):87-100.
    The distinction between personal level explanations and subpersonal ones has been subject to much debate in philosophy. We understand it as one between explanations that focus on an agent’s interaction with its environment, and explanations that focus on the physical or computational enabling conditions of such an interaction. The distinction, understood this way, is necessary for a complete account of any agent, rational or not, biological or artificial. In particular, we review some recent research in Artificial Life that pretends to (...)
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  47. Fred Delcomyn (2001). Biorobotic Models Can Contribute to Neurobiology. Behavioral and Brain Sciences 24 (6):1056-1057.
    The idea that biorobots can be used as a testbed for the evaluation of hypotheses about how an animal functions is supported. Generation of realistic feedback is a major advantage of biorobotic models. Nevertheless, skeptics can only be convinced that this approach is valid if significant biological insights are generated from its application.
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  48. 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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  49. Daniel C. Dennett (1990). Artificial Life: A Feast for the Imagination. [REVIEW] Biology and Philosophy 5 (4):489-492.
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  50. Alan Dorin, Metacreation : Art and Artificial Life.
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