1.
Wiener, N.: Cybernetics: or Control and Communication in the Animal and the Machine. MIT Press, Cambridge (1948)
2.
Turing, A.M.: Computing machinery and intelligence. Mind 59, 433–460 (1950)
MathSciNetCrossRef3.
Merleau-Ponty, M.: Phenomenology of Perception (in French). Gallimard, Paris (1945)
4.
Kolmogorov, A.N.: Three approaches to the quantitative definition of information. Problems Inform. Transmission 1(1), 1–7 (1965)
MathSciNet5.
Chaitin, G.J.: On the length of programs for computing finite binary sequences: statistical considerations. J. Assoc. Comput. Mach. 16, 145–159 (1969)
MathSciNetMATHCrossRef6.
Hommel, B.: Becoming an intentional agent: The emergence of voluntary action. In: 5th eu Cognition Six Monthly Meeting euCognition, Munchen (2008)
7.
Biro, S., Hommel, B. (eds.): Becoming an intentional agent: Early development of action interpretation and action control. Special issue of Acta Psychologica (2007)
8.
Biro, S., Hommel, B.: Becoming an intentional agent: Introduction to the special issue. Acta Psychologica 124, 1–7 (2007)
CrossRef9.
Hoffmann, J.: Anticipatory Behavioral Control. In: Butz, M.V., Sigaud, O., Gérard, P. (eds.) Anticipatory Behavior in Adaptive Learning Systems. LNCS (LNAI), vol. 2684, pp. 44–65. Springer, Heidelberg (2003)
CrossRef10.
Butz, M.V., Sigaud, O., Gérard, P.: Internal Models and Anticipations in Adaptive Learning Systems. In: Butz, M.V., Sigaud, O., Gérard, P. (eds.) Anticipatory Behavior in Adaptive Learning Systems. LNCS (LNAI), vol. 2684, pp. 86–109. Springer, Heidelberg (2003)
CrossRef11.
George, D., Hawkins, J.: A hierarchical Bayesian model of invariant pattern recognition in the visual cortex. In: Proceedings of the International Joint Conference on Neural Net works. IEEE, Los Alamitos (2005)
12.
Van Essen, D.C., Anderson, C.H., Felleman, D.J.: Information processing in the primate visual system: an integrated systems perspective. Science 255(5043), 419–423 (1992)
CrossRef13.
Fukushima, K.: Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biological Cybernetics 36(4), 193–202 (1980)
MATHCrossRef14.
Hawkins, J., Blakeslee, S.: On Intelligence. Times Books, Henry Holt and Company (2004)
15.
Lee, T.S., Mumford, D.: Hierarchical Bayesian inference in the visual cortex. J. Opt. Soc. Am. A. Opt. Image Sci. Vis. 20(7), 1434–1448 (2003)
CrossRef16.
Pearl, J.: Probabilistic Reasoning in Intelligent Systems. MorganKaufman Publishers, San Francisco (1988)
17.
Riesenhuber, M., Poggio, T.: Hierarchical models of object recognition in cortex. Nature Neuroscience 2(11), 1019–1025 (1999)
CrossRef18.
Stringer, S.M., Rolls, E.T.: Invariant object recognition in the visual system with novel views of 3D objects. Neural Computation 14(11), 2585–2596 (2002)
MATHCrossRef19.
Bernardet, U., Bermudez i Badia, S., Verschure, P.F.M.J.: A model for the neuronal substrate of dead reckoning and memory in arthropods: a comparative computational and behavioral study. Theory in Biosciences 127 (2008)
20.
Verschure, P.F.M.J.: Building a Cyborg: A Brain Based Architecture for Perception, Cognition and Action, Keynote talk. In: IROS 2008, Nice (2008)
21.
Brooks, R.: A Robust Layered Control System for A Mobile Robot. IEEE Journal of Robotics and Automation (1986)
22.
Pfeifer, R.: Cheap designs: exploiting the dynamics of the system-environment interaction. Three case studies on navigation. In: Conference on Prerational Intelligence — Pheno- monology of Complexity Emerging in Systems of Agents Interacting Using Simple Rules, Center for Interdisciplinary Research, University of Bielefeld, pp. 81–91 (1993)
23.
Pfeifer, R., Iida, F.: Embodied Artificial Intelligence: Trends and Challenges. In: Iida, F., Pfeifer, R., Steels, L., Kuniyoshi, Y. (eds.) Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139, pp. 1–26. Springer, Heidelberg (2004)
CrossRef24.
Lungarella, M., Iida, F., Bongard, J., Pfeifer, R. (eds.): 50 Years of AI. Springer, Heidelberg (2007)
25.
Touchette, H., Lloyd, S.: Information-theoretic approach to the study of control systems. Physica A 331, 140–172 (2003)
MathSciNetCrossRef26.
Gomez, G., Lungarella, M., Tarapore, D.: Information-theoretic approach to embodied category learning. In: Proc. of 10th Int. Conf. on Artificial Life and Robotics, pp. 332–337 (2005)
27.
Philipona, D., O’ Regan, J.K., Nadal, J.-P., Coenen, O.J.-M.D.: Perception of the structure of the physical world using unknown multimodal sensors and effectors. In: Advances in Neural Information Processing Systems (2004)
28.
Olsson, L., Nehaiv, C.L., Polani, D.: Information Trade-Offs and the Evolution of Sensory Layouts. In: Proc. Artificial Life IX (2004)
29.
Bonsignorio, F.P.: Preliminary Considerations for a Quantitative Theory of Networked Embodied Intelligence. In: Lungarella, M., Iida, F., Bongard, J.C., Pfeifer, R. (eds.) 50 Years of Aritficial Intelligence. LNCS (LNAI), vol. 4850, pp. 112–123. Springer, Heidelberg (2007)
CrossRef30.
Burfoot, D., Lungarella, M., Kuniyoshi, Y.: Toward a Theory of Embodied Statistical Learning. In: Asada, M., Hallam, J.C.T., Meyer, J.-A., Tani, J. (eds.) SAB 2008. LNCS (LNAI), vol. 5040, pp. 270–279. Springer, Heidelberg (2008)
CrossRef31.
Garcia, M., Chatterjee, A., Ruina, A., Coleman, M.: The Simplest Walking Model: Stability, Complexity, and Scaling, Transactions of the ASME. Journal of Biomechanical Engineering 120, 281–288 (1998)
CrossRef32.
33.
Lloyd, S.: Measures of Complexity: A Non exhaustive List. IEEE Control Systems Magazine (2001)
34.
Rosenblatt, F.: The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain, Cornell Aeronautical Laboratory. Psychological Review 65(6), 386–408 (1958)
MathSciNetCrossRef35.
Potter, S.M.: What Can AI Get from Neuroscience? In: Lungarella, M., Iida, F., Bongard, J.C., Pfeifer, R. (eds.) 50 Years of Aritficial Intelligence. LNCS (LNAI), vol. 4850, pp. 174–185. Springer, Heidelberg (2007)
CrossRef36.
Bach-y-Rita, P.: Brain Mechanisms in Sensory Substitution. Academic Press, New York (1972)
37.
Der, R.: Self-organized acquisition of situated behavior. Theory in Biosciences 120, 179–187 (2001)
38.
Der, R.: Artificial Life from the principle of homeokinesis. In: Proceedings of the German Workshop on Artificial Life (2008)
39.
Prokopenko, M., Gerasimov, V., Tanev, I.: Evolving Spatiotemporal Coordination in a Modular Robotic System. In: Nolfi, S., Baldassarre, G., Calabretta, R., Hallam, J.C.T., Marocco, D., Meyer, J.-A., Miglino, O., Parisi, D. (eds.) SAB 2006. LNCS (LNAI), vol. 4095, pp. 558–569. Springer, Heidelberg (2006)
CrossRef40.
Hornik, K., Stinchcombe, M., White, H.: Multilayer feedforward networks are universal approximators. Neural Networks 2, 359–366 (1989)
CrossRef41.
Steels, L.: Semiotic dynamics for embodied agents. IEEE Intelligent Systems, 32–38 (2006)
42.
Rus, D.L.: Robotics as Computation for Interaction with the Physical World. In: Special Session on CyberPhysical Systems. IEEE/RSJ 2008, Nice (2008)
43.
Markus, G.F.: The Haphazard construction of the human mind. Houghton Mifflin, New York (2008)
44.
Tononi, G.: Consciousness as integrated information: a provisional manifesto. Biological Bulletin 215, 216–242 (2008)
CrossRef45.
Ferrucci, D., Brown, E., Chu-Carroll, J., Fan, J., Gondek, D., Kalyanpur, A.A., Lally, A., Murdock, J.W., Nyberg, E., Prager, J., Schlaefer, N., Welty, C.: Building Watson: An Overview of the DeepQA Project. AI Magazine Fall (2010)
46.
Berthoz, A.: The Brain’s sense of movement. Harvard University Press, Harvard (2000)
47.
Amorim, M.A., Glasauer, S., Corpinot, K., Berthoz, A.: Updating an object’s orientation and location during non visual navigation: a comparison between two processing modes. Percept. Psychopys. 59, 404–418 (1997)
CrossRef48.
Berthoz, A.: Neurobiology of "Umwelt" How Living Beings Perceive the World. In: Berthoz, A., Christen, Y. (eds.), Springer (2009)
49.
Dodig-Crnkovic, G., Mueller, V.C.: A Dialogue Concerning Two World Systems: Info-Computational vs. Mechanistic,
http://arxiv.org/abs/0910.5001
50.
Bonsignorio, F.P.: Steps to a Cyber-Physical Model of Networked Embodied Anticipatory Behavior. In: Pezzulo, G., Butz, M.V., Sigaud, O., Baldassarre, G. (eds.) ABiALS 2008. LNCS (LNAI), vol. 5499, pp. 77–94. Springer, Heidelberg (2009)
51.
Amigoni, F., Reggiani, M., Schiaffonati, V.: An insightful comparison between experiments in mobile robotics and in science. Auton. Robots 27(4), 313–325 (2009)
CrossRef52.
Chirikjian, G.S.: Information Theory on Lie-groups and Mobile Robotics Applications. In: Proceedings of ICRA 2010, Anchorage, AK (2010)
53.
Chaumette, F., Hutchinson, S.: Visual Servoing and Tracking. In: Siciliano, B., Khatib, O. (eds.) Handbook of Robotics. Springer, Berlin (2008)
54.
Nelissen, K., Luppino, G., Vanduffel, W., Rizzolatti, G., Orban, G.A.: Observing Others: Multiple Action Representation in the Frontal Lobe. Science 310(5746), 332–336 (2005)
CrossRef55.
Wolpert, D.M., Diedrichsen, J., Flanagan, J.R.: Principles of sensorimotor learning. Nature Reviews Neuroscience 12, 739–751 (2011)
56.
Rowe, T.B., Macrini, T.E., Luo, Z.: Fossil Evidence on Origin of the Mammalian Brain. Science 332(6032), 955–957 (2011)
CrossRef57.
Pastra, K.: Personal communication (2010)
58.
Bickhard, M.H., Terveen, L.: Foundational issues in artificial intelligence and cognitive science. Elsevier, Amsterdam (1995)
59.
Shannon, C.E.: The Mathematical Theory of Communication. Bell Sys. Tech. J. 27, 623 (1948)
MathSciNet60.
61.
von Uexküll, J.: A Stroll Through the Worlds of Animals and Men: A Picture Book of Invisible Worlds. In: Schiller, C.H. (ed.) Instinctive Behavior: The Development of a Modern Concept, pp. 5–80. International Universities Press, Inc., New York (1957)
62.
Damasio, A.: Descartes’ Error: Emotion, Reason, and the Human Brain, Putnam (1994)
63.
Berthoz, A., Weiss, G.: Simplexity. Yale University Press, Yale (2012)
64.
Einstein, A.: Obituary for physicist and philosopher Ernst Mach. Physikalische Zeitschrift 17 (1916)
65.
Simon, H.: The architecture of complexity. Proc. Am. Phil. Soc. 106 (1962)
66.
Ashby, W.R.: Design for a Brain. Chapman and Hill, London (1954)
67.
Turing, A.M.: Computing machinery and intelligence. Mind 59, 433–460 (1950)
MathSciNetCrossRef68.
Eddington, A.S.: The Nature of the Physical World (1928)
69.
Bateson, G.: Steps to an Ecology of Mind. University of Chicago Press, Chicago (1972)
70.
Marx, K.: Capital, vol. I (in German), Hamburg (1867)
71.
Kant, I.: Critique of Pure Reason (in German: Kritik der reinen Vernunft) (1781,1787)
72.
Hume, D.: A Treatise of Human Nature: Being an Attempt to introduce the experimental Method of Reasoning into Moral Subjects (1739-1740)
73.
Augustine of Hippo: Confessions (397-398)
74.
Aristotle: Politics, Book 1, 1253b (322 BC)