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  1. Jos J. Adam & Ron F. Keulen (2004). FMRI Evidence for and Behavioral Evidence Against the Planning–Control Model. Behavioral and Brain Sciences 27 (1):24-24.
    Consistent with the planning–control model, recent fMRI data reveal that the inferior parietal lobe, the frontal lobes, and the basal ganglia are involved in motor planning. Inconsistent with the planning–control model, however, recent behavioral data reveal a spatial repulsion effect, indicating that the visual context surrounding the target can sometimes influence the on-line control of goal-directed action.
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  2. Bryan Adams, Rodney A. Brooks & Brian Scassellati, Humanoid Robots: A New Kind of Tool.
    In his 1923 play R.U.R.: Rossum s Universal Robots, Karel Capek coined robot as a derivative of the Czech robota (forced labor). Limited to work too tedious or dangerous for humans, today s robots weld parts on assembly lines, inspect nuclear plants, and explore other planets. Generally, robots are still far from achieving their fictional counterparts intelligence and flexibility. Humanoid robotics labs worldwide are working on creating robots that are one step closer to science fiction s androids. Building a humanlike (...)
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  3. Nicholas Agar (2012). On the Irrationality of Mind-Uploading: A Rely to Neil Levy. [REVIEW] AI and Society 27 (4):431-436.
    In a paper in this journal, Neil Levy challenges Nicholas Agar’s argument for the irrationality of mind-uploading. Mind-uploading is a futuristic process that involves scanning brains and recording relevant information which is then transferred into a computer. Its advocates suppose that mind-uploading transfers both human minds and identities from biological brains into computers. According to Agar’s original argument, mind-uploading is prudentially irrational. Success relies on the soundness of the program of Strong AI—the view that it may someday be possible to (...)
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  4. Michael Anderson, Circuit Sharing and the Implementation of Intelligent Systems.
    One of the most foundational and continually contested questions in the cognitive sciences is the degree to which the functional organization of the brain can be understood as modular. In its classic formulation, a module was defined as a cognitive sub-system with (all or most of) nine specific properties; the classic module is, among other things, domain specific, encapsulated (i.e. maintains proprietary representations to which other modules have no access), and implemented in dedicated neural substrates. Most of the examinations—and especially (...)
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  5. Michael Anderson, Projects.
    Description: The massive redeployment hypothesis (MRH) is a theory about the functional organization of the human cortex, offering a middle course between strict localization on the one hand, and holism on the other. Central to MRH is the claim that cognitive evolution proceeded in a way analogous to component reuse in software engineering, whereby existing components—originally developed to serve some specific purpose—were used for new purposes and combined to support new capacities, without disrupting their participation in existing programs.
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  6. Susan Leigh Anderson (2011). Once People Understand That Machine Ethics is Concerned with How Intelligent Machines Should Behave, They Often Maintain That Isaac Asimov has Already Given Us an Ideal Set of Rules for Such Machines. They Have in Mind Asimov's Three Laws of Robotics: 1. A Robot May Not Injure a Human Being, or, Through Inaction, Allow a Human. In M. Anderson S. Anderson (ed.), Machine Ethics. Cambridge Univ. Press.
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  7. Susan Leigh Anderson (2011). Philosophical Concerns with Machine Ethics. In M. Anderson S. Anderson (ed.), Machine Ethics. Cambridge Univ. Press.
  8. Ian O. Angell (2010). Science's First Mistake: Delusions in Pursuit of Theory. Bloomsbury Academic.
    because whenever an observer observes, he creates a contingent distinction between what is observed and what is by necessity left unobserved. ...
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  9. Colin M. Angle & Rodney A. Brooks, Small Planetary Rovers.
    We have previously built a small IKg ([Angle 89] and [Brooks 89]) six legged walking robot named Genghis. It was remarkably successful as a testbed to develop walking and learning algorithms. It encouraged us to build a more fully engineered robot with higher performance. We are building two copies of the robot, both 1.6Kg in mass. Their generic name is Attila. Attila has 24 actuators and over 150 sensors, all connected via a local network (the I2C bus) to 11 onboard (...)
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  10. Stuart Armstrong, Anders Sandberg & Nick Bostrom (2012). Thinking Inside the Box: Controlling and Using an Oracle AI. [REVIEW] Minds and Machines 22 (4):299-324.
    There is no strong reason to believe that human-level intelligence represents an upper limit of the capacity of artificial intelligence, should it be realized. This poses serious safety issues, since a superintelligent system would have great power to direct the future according to its possibly flawed motivation system. Solving this issue in general has proven to be considerably harder than expected. This paper looks at one particular approach, Oracle AI. An Oracle AI is an AI that does not act in (...)
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  11. Peter M. Asaro (2001). Hans Moravec, Robot. Mere Machine to Transcendent Mind, New York, NY: Oxford University Press, Inc., 1999, IX + 227 Pp., $25.00 (Cloth), ISBN 0-19-511630-. [REVIEW] Minds and Machines 11 (1):143-147.
  12. Harald Atmanspacher, Correlates of Perceptive Instabilities in Event-Related Potentials.
    The study of instabilities in perception has attracted much interest in recent decades. The presented investigations focus on electrophysiological correlates of orientation reversals of both ambiguous visual stimuli and alternating non-ambiguous stimuli, representing the two options of the ambiguous version. Based on a refined experimental setup, significant features in the event-related potentials associated with the perception of orientation reversal were found in both cases. Their occipital location, their early occurence (200–250 ms), and their latency difference (50 ms) offer interesting perspectives (...)
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  13. Harald Atmanspacher (2005). Acategoriality as Mental Instability. Journal of Mind and Behavior 26 (3):181.
    Mental representations are based upon categories in which the state of a mental system is stable. Acategorial states, on the other hand, are distinguished by unstable behavior. A refined and compact terminology for the description of categorial and acategorial mental states and their stability properties is introduced within the framework of the theory of dynamical systems. The relevant concepts are illustrated by selected empirical observations in cognitive neuroscience. Alterations of the category of the first person singular and features of creative (...)
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  14. Neil Badmington (ed.) (2000). Posthumanism. Palgrave.
    What is posthumanism and why does it matter? This book offers an introduction to the ways in which humanism's belief in the natural supremacy of the Family of Man has been called into question at different moments and from different theoretical positions. What is the relationship between posthumanism and technology? Can posthumanism have a politics—postcolonial or feminist? Are postmodernism and poststructuralism posthumanist? What happens when critical theory meets Hollywood cinema? What links posthumanism to science fiction. Posthumanism addresses these and other (...)
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  15. Michael Baumann (2000). LEGO® Mindstorms, Robotics Invention System 1.5. Complexity 5 (6):48-50.
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  16. Raymond Bayer (1957). L'évolution de l'Intelligence Et Les Formes Modernes de la Dialectique. Dialectica 11 (3‐4):296-305.
    RésuméIl y a, dans la notion de dialectique moderne, deux perspectives de l'évolution intellectuelle: l'intelligence peut n'ětre encore que la pointe extrěme de l'adaptation biologique ou elle peut ětre déjà l'expression de la raison. C'est ce caractère ouvert des dialectiques scientifiques que nous retrouvons dans les interprétations étudiées ici: le pancalisme de Baldwin, la pensée sans images de Binet, l'interprétation de Janet et celle de Piaget, qui contribuent à enrichir la notion de genèse de l'intelligence et à en faire saisir (...)
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  17. Barbara Becker (2006). Social Robots-Emotional Agents: Some Remarks on Naturalizing Man-Machine Interaction. International Review of Information Ethics 6:37-45.
    The construction of embodied conversational agents - robots as well as avatars - seem to be a new challenge in the field of both cognitive AI and human-computer-interface development. On the one hand, one aims at gaining new insights in the development of cognition and communication by constructing intelligent, physical instantiated artefacts. On the other hand people are driven by the idea, that humanlike mechanical dialog-partners will have a positive effect on human-machine-communication. In this contribution I put for discussion whether (...)
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  18. Andrew beedle (1998). Sixteen Years of Artificial Intelligence: Mind Design and Mind Design II. Philosophical Psychology 11 (2):243 – 250.
    John Haugeland's Mind design and Mind design II are organized around the idea that the fundamental idea of cognitive science is that, “intelligent beings are semantic engines — in other words, automatic formal systems with interpretations under which they consistently make sense”. The goal of artificial intelligence research, or the problem of “mind design” as Haugeland calls it, is to develop computers that are in fact semantic engines. This paper canvasses the changes in artificial intelligence research reflected in the different (...)
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  19. Sander Begeer (2005). Book Reviews - Roberto Cordeschi, the Discovery of the Artificial: Behaviour, Mind and Machines Before and Beyond Cybernetics, Dordrecht, the Netherlands: Kluwer Academic Publishers, 2002, XX + 312, ISBN 1-4020-0606-. [REVIEW] Minds and Machines 15 (2):264-268.
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  20. Maria Bittner (2006). Ontology for Human Talk and Thought (Not Robotics). Theoretical Linguistics 32 (1):47-56.
    Hamm, Kamp, and van Lambalgen 2006 (hereafter HLK) propose to relate NL discourse to cognitive representations that also deal with world knowledge, planning, belief revision, etc. Surprisingly, to represent human cognition they use an event calculus "which has found applications in robotics". This comment argues that the robotics-based theory of HLK attributes too much to world knowledge and not enough to the ontology, centering, and other universals of NL semantics. It is also too Anglo-centric to generalize to languages of other (...)
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  21. Russell Blackford & Damien Broderick (eds.) (2014). Intelligence Unbound: The Future of Uploaded and Machine Minds. Wiley-Blackwell.
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  22. Margaret Boden (2006). Of Islands and Interactions. Journal of Consciousness Studies 13 (5):53-63.
    John Ziman-- the much-missed-- reminds us that 'no man is an island', and takes us to task for working from an individualistic theoretical base. That 'us' includes nearly all social scientists, and most Anglo-American philosophers too. For sure, it includes cognitive scientists, who theorize people in terms of concepts drawn from cybernetics and/or artificial intelligence. (I'll use the term 'computational concepts' broadly, to cover both types.) Indeed, it's a common complaint that cognitive science is overly individualistic.
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  23. Margaret A. Boden (1995). Could a Robot Be Creative--And Would We Know? In Android Epistemology. Cambridge: MIT Press.
  24. Margaret A. Boden (ed.) (1990). The Philosophy of Artificial Intelligence. Oxford University Press.
    This interdisciplinary collection of classical and contemporary readings provides a clear and comprehensive guide to the many hotly-debated philosophical issues at the heart of artificial intelligence.
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  25. Maria G. Bonome (2011). Prediction and Prescription in the Science of the Artificial: Information Science and Complexity1. In Dennis Dieks, Wenceslao Gonzalo, Thomas Uebel, Stephan Hartmann & Marcel Weber (eds.), Explanation, Prediction, and Confirmation. Springer. 331--343.
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  26. Nick Bostrom (2005). — ŽŽ—œŽ ˜ ˜œ‘ž–Š— ’—’In Defence of Posthuman Dignity. Bioethics 19 (3):202-214.
    Positions on the ethics of human enhancement technologies can be (crudely) characterized as ranging from transhumanism to bioconservatism. Transhumanists believe that human enhancement technologies should be made widely available, that individuals should have broad discretion over which of these technologies to apply to themselves, and that parents should normally have the right to choose enhancements for their children-to-be. Bioconservatives (whose ranks include such diverse writers as Leon Kass, Francis Fukuyama, George Annas, Wesley Smith, Jeremy Rifkin, and Bill McKibben) are generally (...)
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  27. Matthew Botvinick (2012). Commentary: Why I Am Not a Dynamicist. Topics in Cognitive Science 4 (1):78-83.
    The dynamical systems approach in cognitive science offers a potentially useful perspective on both brain and behavior. Indeed, the importation of formal tools from dynamical systems research has already paid off for our field in many ways. However, like some other theoretical perspectives in cognitive science, the dynamical systems approach comes in both moderate or pragmatic and “fundamentalist” varieties (Jones & Love, 2011). In the latter form, dynamical systems theory can rise to some stirring rhetorical heights. However, as argued here, (...)
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  28. Bouscaren (1926). Proteus, or The Future of Intelligence. Modern Schoolman 2 (4):59-61.
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  29. William F. Brewer (1999). Perceptual Symbols: The Power and Limitations of a Theory of Dynamic Imagery and Structured Frames. Behavioral and Brain Sciences 22 (4):611-612.
    The perceptual symbol approach to knowledge representation combines structured frames and dynamic imagery. The perceptual symbol approach provides a good account of the representation of scientific models, of some types of naive theories held by children and adults, and of certain reconstructive memory phenomena. The ontological status of perceptual symbols is unclear and this form of representation does not succeed in accounting for all forms of human knowledge.
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  30. Selmer Bringsjord (2004). On Building Robot Persons: Response to Zlatev. [REVIEW] Minds and Machines 14 (3):381-385.
    Zlatev offers surprisingly weak reasoning in support of his view that robots with the right kind of developmental histories can have meaning. We ought nonetheless to praise Zlatev for an impressionistic account of how attending to the psychology of human development can help us build robots that appear to have intentionality.
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  31. Rodney A. Brooks, Technologies for Human/Humanoid Natural Interactions.
    There are a number of reasons to be interested in building humanoid robots. They include (1) since almost all human artifacts have been designed to easy for humans to interact with, humanoid robots provide backward compatibility with the existing human constructed world, (2) humanoid robots provide a natural form for humans to operate through telepresence since they have the same kinematic design as humans themselves, (3) by building humanoid robots that model humans directly they will be a useful tool in (...)
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  32. Rodney A. Brooks, A Robot That Walks; Emergent Behaviors From a Carefully Evolved Network.
    Most animals have significant behavioral expertise built in without having to explicitly learn it all from scratch. This expertise is a product of evolution of the organism; it can be viewed as a very long term form of learning which provides a structured system within which individuals might learn more specialized skills or abilities. This paper suggests one possible mechanism for analagous robot evolution by describing a carefully designed series of networks, each one being a strict augmentation of the previous (...)
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  33. Rodney A. Brooks, How to Build Complete Creatures Rather Than Isolated Cognitive Simulators.
    Artificial Intelligence as a discipline has gotten bogged down in subproblems of intelligence. These subproblems are the result of applying reductionist methods to the goal of creating a complete artificial thinking mind. In Brooks (1987) 1 have argued that these methods will lead us to solving irrelevant problems; interesting as intellectual puzzles, but useless in the long run for creating an artificial being.
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  34. Rodney A. Brooks, Learning to Coordinate Behaviors.
    We describe an algorithm which allows a behavior-based robot to learn on the basis of positive and negative feedback when to activate its behaviors. In accordance with the philosophy of behavior-based robots, the algorithm is completely distributed: each of the behaviors independently tries to find out (i) whether it is relevant (ie. whether it is at all correlated to positive feedback) and (ii) what the conditions are under which it becomes reliable (i.e. the conditions under which i t maximizes the (...)
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  35. Rodney A. Brooks, Prospects for Human Level Intelligence for Humanoid Robots.
    Both direct, and evolved, behavior-based approaches to mobile robots have yielded a number of interesting demonstrations of robots that navigate, map, plan and operate in the real world. The work can best be described as attempts to emulate insect level locomotion and navigation, with very little work on behavior-based non-trivial manipulation of the world. There have been some behavior-based attempts at exploring social interactions, but these too have been modeled after the sorts of social interactions we see in insects. But (...)
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  36. Rodney A. Brooks, The Intelligent Room Project.
    At the MIT Arti cial Intelligence Laboratory we have been working on technologies for an Intelligent Room. Rather than pull people into the virtual world of the computer we are trying to pull the computer out into the real world of people. To do this we are combining robotics and vision technology with speech understanding systems, and agent based architectures to provide ready at hand computation and information services for people engaged in day to day activities, both on their own (...)
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  37. Rodney A. Brooks, The Role of Learning in Autonomous Robots.
    Applications of learning to autonomous agents (simulated or real) have often been restricted to learning a mapping from perceived state of the world to the next action to take. Often this is couched in terms of learning from no previous knowledge. This general case for real autonomous robots is very difficult. In any case, when building a real robot there is usually a lot of a priori knowledge (e.g., from the engineering that went into its design) which doesn’t need to (...)
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  38. Rodney A. Brooks & Liana M. Lorigo, Visually-Guided Obstacle Avoidance in Unstructured Environments.
    This paper presents an autonomous vision-based obstacle avoidance system. The system consists of three independent vision modules for obstacle detection, each of which is computationally simple and uses a di erent criterion for detection purposes. These criteria are based on brightness gradients, RGB Red, Green, Blue color, and HSV Hue, Saturation, Value color, respectively. Selection of which modules are used to command the robot proceeds exclusively from the outputs of the modules themselves. The system is implemented on a small monocular (...)
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  39. John Bryant (1991). Systems Theory and Scientific Philosophy: An Application of the Cybernetics of W. Ross Ashby to Personal and Social Philosophy, the Philosophy of Mind, and the Problems of Artificial Intelligence. University Press of America.
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  40. Joanna J. Bryson (2010). Why Robot Nannies Probably Won't Do Much Psychological Damage. Interaction Studies 11 (2):196-200.
  41. Joanna J. Bryson (2006). The Attentional Spotlight. Minds and Machines 16 (1):21-28.
    One of the interesting and occasionally controversial aspects of Dennett’s career is his direct involvement in the scientific process. This article describes some of Dennett’s participation on one particular project conducted at MIT, the building of the humanoid robot named Cog. One of the intentions of this project, not to date fully realized, was to test Dennett’s multiple drafts theory of consciousness. I describe Dennett’s involvement and impact on Cog from the perspective of a graduate student. I also describe the (...)
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  42. Daniela Cerqui, Jutta Weber & Karsten Weber (2006). Ethics in Robotics. International Review of Information Ethics 2:2006.
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  43. William C. Charron (1972). "Brain, Mind and Computers," by Stanley L. Jaki. Modern Schoolman 49 (3):270-273.
  44. Yoonsuck Choe (2006). How Neural is the Neural Blackboard Architecture? Behavioral and Brain Sciences 29 (1):72-73.
    The target article does not provide insight into how the proposed neural blackboard architecture can be mapped to known neural structures in the brain. There are theories suggesting that the thalamus may be a good candidate. However, the experimental evidence suggests that the cortex may be involved (if in fact the blackboard is implemented in the brain). Issues arising from such a mapping will be discussed.
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  45. Samir Chopra & Laurence White, Privacy and Artificial Agents, or, is Google Reading My Email?
    in Proceedings of the International Joint Conference on Artificial Intelligence, 2007.
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  46. Ronald L. Chrisley (1998). What Might Dynamical Intentionality Be, If Not Computation? Behavioral and Brain Sciences 21 (5):634-635.
    (1) Van Gelder's concession that the dynamical hypothesis is not in opposition to computation in general does not agree well with his anticomputational stance. (2) There are problems with the claim that dynamic systems allow for nonrepresentational aspects of computation in a way in which digital computation cannot. (3) There are two senses of the “cognition is computation” claim and van Gelder argues against only one of them. (4) Dynamical systems as characterized in the target article share problems of universal (...)
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  47. Brian Christian (2011). The Most Human Human: What Talking with Computers Teaches Us About What It Means to Be Alive. Doubleday.
  48. Andy Clark (2008). The Frozen Cyborg: A Reply to Selinger and Engström. [REVIEW] Phenomenology and the Cognitive Sciences 7 (3):343-346.
    Selinger and Engstrom, A moratorium on cyborgs: Computation, cognition and commerce, 2008 (this issue) urge upon us a moratorium on ‘cyborg discourse’. But the argument underestimates the richness and complexity of our ongoing communal explorations. It leans on a somewhat outdated version of the machine metaphor (exemplified perhaps by a frozen 1970’s Cyborg). The modern cyborg, informed by an evolving computational model of mind, can play a positive role in the critical discussions that Selinger and Engstrom seek.
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  49. B. Clarke (2012). From Information to Cognition: The Systems Counterculture, Heinz von Foerster's Pedagogy, and Second-Order Cybernetics. Constructivist Foundations 7 (3):196-207.
    Context: In this empirical and conceptual paper on the historical, philosophical, and epistemological backgrounds of second-order cybernetics, the emergence of a significant pedagogical component to Heinz von Foerster’s work during the last years of the Biological Computer Laboratory is placed against the backdrop of social and intellectual movements on the American landscape. Problem: Previous discussion in this regard has focused largely on the student radicalism of the later 1960s. A wider-angled view of the American intellectual counterculture is needed. However, this (...)
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  50. L. Jonathan Cohen (1986). What Sorts of Machines Can Understand the Symbols They Use? Proceedings of the Aristotelian Society 60:81-96.
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