[CrossRef] 3. Zahedi, K.; Ay, N. Quantifying Morphological Computation. Entropy 2013, 15, 1887-1915. [CrossRef] 4. Nowakowski, P.R. Bodily Processing: The Role of Morphological Computation. Entropy 2017, 19, 295. [CrossRef] 5. Ghazi-Zahedi, K.; Langer, C.; Ay, N. Morphological Computation: Synergy of Body and Brain. Entropy 2017, 19, 456. [CrossRef] 6. Hauser, H.; Füchslin, R.M.; Pfeifer, R. (Eds.) Opinions and Outlooks on Morphological Computation; Zurich, 2014; ISBN 978-3-033-04515-6. Available online: http://www.morphologicalcomputation.org/e-book/ (accessed on 6 December 2018). 7. Müller, V.C.; Hoffmann, M. What is Morphological Computation? On How the Body Contributes to Cognition and Control. Artif. Life 2017, 23, 1-24. [CrossRef] [PubMed] 8. Piccinini, G. Physical Computation: A Mechanistic Account; Oxford University Press: Oxford, UK, 2015. 9. Miłkowski, M. Explaining the Computational Mind; MIT Press: Cambridge, MA, USA, 2013. 10. Pezzulo, G.; Donnarumma, F.; Iodice, P.; Maisto, D.; Stoianov, I. Model-Based Approaches to Active Perception and Control. Entropy 2017, 19, 266. [CrossRef] 11. Pfeifer, R.; Bongard, J. How the Body Shapes the Way We Think; MIT Press: Cambridge, MA, USA, 2007. 12. Zuse, K. The Computer-My Life; Springer: Berlin/Heidelberg, Germany, 1993. 13. Miłkowski, M. Beyond Formal Structure: A Mechanistic Perspective on Computation and Implementation. J. Cogn. Sci. 2011, 12, 359-379. [CrossRef] 14. Füchslin, R.M.; Dzyakanchuk, A.; Flumini, D.; Hauser, H.; Hunt, K.J.; Luchsinger, R.H.; Reller, B.; Scheidegger, S.; Walker, R. Morphological Computation and Morphological Control: Steps Toward a Formal Theory and Applications. Artif. Life 2012, 19, 9-34. [CrossRef] 15. McGeer, T. Passive Dynamic Walking. Int. J. Robot. Res. 1990, 9, 62-82. [CrossRef] 16. Horsman, C.; Stepney, S.; Wagner, R.C.; Kendon, V. When does a physical system compute? Proc. R. Soc. Math. Phys. Eng. Sci. 2014, 470, 20140182. [CrossRef] [PubMed] 17. Piccinini, G. The Mind as Neural Software? Understanding Functionalism, Computationalism, and Computational Functionalism. Philos. Phenomenol. Res. 2010, 81, 269-311. [CrossRef] 18. Churchland, P.S.; Sejnowski, T.J. The Computational Brain; MIT Press: Cambridge, MA, USA, 1992. 19. Shagrir, O. Computation, San Diego Style. Philos. Sci. 2010, 77, 862-874. [CrossRef] 20. Shagrir, O. In defense of the semantic view of computation. Synthese 2018, 1-26. [CrossRef] 21. Sprevak, M. Computation, individuation, and the received view on representation. Stud. Hist. Philos. Sci. Part A 2010, 41, 260-270. [CrossRef] 22. Miłkowski, M. Objections to Computationalism: A Survey. Rocz. Filoz. 2018, 66, 57-75. [CrossRef] 23. Godfrey-Smith, P. Triviality arguments against functionalism. Philos. Stud. 2008, 145, 273-295. [CrossRef] 24. Searle, J.R. The Rediscovery of the Mind; MIT Press: Cambridge, MA, USA, 1992. 25. Putnam, H. Representation and Reality; The MIT Press: Cambridge, MA, USA, 1991. 26. Buechner, J. Godel, Putnam, and Functionalism: A New Reading of Representation and Reality; MIT Press: Cambridge, MA, USA, 2008. 27. Piccinini, G. Computation in Physical Systems. In The Stanford Encyclopedia of Philosophy; Zalta, E.N., Ed.; Stanford University Press: Redwood City, CA, USA, 2010. 28. Newman, M.H.A. Mr. Russell's “Causal Theory of Perception”. Mind 1928, 37, 137-148. [CrossRef] 29. Copeland, B.J. What is computation? Synthese 1996, 108, 335-359. [CrossRef] 30. Chalmers, D.J. Does a rock implement every finite-state automaton? Synthese 1996, 108, 309-333. [CrossRef] 31. Millhouse, T. A Simplicity Criterion for Physical Computation. Br. J. Philos. Sci. 2017, axx046. [CrossRef] 32. Grabarczyk, P. O niearbitralnym kryterium posiadania struktury obliczeniowej. Filoz. Nauki 2013, 4, 31-50. 33. MacKay, D.M. Information, Mechanism and Meaning; MIT Press: Cambridge, MA, USA, 1969. 34. Dewhurst, J. Computing Mechanisms Without Proper Functions. Minds Mach. 2018, 28, 569-588. [CrossRef] 35. Garson, J. The Functional Sense of Mechanism. Philos. Sci. 2013, 80, 317-333. [CrossRef] Entropy 2018, 20, 942 17 of 18 36. Krohs, U. Functions as based on a concept of general design. Synthese 2009, 166, 69-89. [CrossRef] 37. Cummins, R. Functional Analysis. J. Philos. 1975, 72, 741-765. [CrossRef] 38. Craver, C.F. Mechanisms and natural kinds. Philos. Psychol. 2009, 22, 575-594. [CrossRef] 39. Piccinini, G. The Physical Church-Turing Thesis: Modest or Bold? Br. J. Philos. Sci. 2011, 62, 733-769. [CrossRef] 40. Crutchfield, J.P.; Ditto, W.L.; Sinha, S. Introduction to Focus Issue: Intrinsic and Designed Computation: Information Processing in Dynamical Systems—Beyond the Digital Hegemony. Chaos Interdiscip. J. Nonlinear Sci. 2010, 20, 037101. [CrossRef] 41. Dodig-Crnkovic, G.; Müller, V.C. A Dialogue Concerning Two World Systems: Info-Computational vs. Mechanistic. In Information and Computation; Dodig-Crnkovic, G., Burgin, M., Eds.; World Scientific Publishing: Singapore, 2010. 42. Anderson, N.G.; Piccinini, G. Pancomputationalism and the Computational Description of Physical Systems. Available online: http://philsci-archive.pitt.edu/12812/ (accessed on 14 October 2018). 43. Müller, V.C. Pancomputationalism: Theory or metaphor? In Philosophy, Computing and Information Science; Hagengruber, R., Riss, U., Eds.; Pickering & Chattoo: London, UK, 2014; pp. 213-222. 44. Friston, K. Life as we know it. J. R. Soc. Interface 2013, 10, 20130475. [CrossRef] 45. Michelsen, A.; Popov, A.V.; Lewis, B. Physics of directional hearing in the cricket Gryllus bimaculatus. J. Comp. Physiol. A 1994, 175, 153-164. [CrossRef] 46. Webb, B. Using robots to model animals: a cricket test. Robot. Auton. Syst. 1995, 16, 117-134. [CrossRef] 47. Torben-nielsen, B.; Webb, B.; Reeve, R. New Ears for a Robot Cricket. In Artificial Neural Networks: Biological ˙ Inspirations; Duch, W., Kacprzyk, J., Oja, E., Zadrozny, S., Eds.; Springer: Berlin/Heidelberg, Germany, 2005; Volume 3696, pp. 297-304. 48. Paquot, Y.; Duport, F.; Smerieri, A.; Dambre, J.; Schrauwen, B.; Haelterman, M.; Massar, S. Optoelectronic Reservoir Computing. Sci. Rep. 2012, 2, 287. [CrossRef] [PubMed] 49. Hoffmann, M.; Müller, V.C. Trade-offs in exploiting body morphology for control: From simple bodies and model-based control to complex ones with model-free distributed control schemes. In E-book on Opinions and Outlook on Morphological Computation; Hauser, H., Füchslin, R.M., Pfeifer, R., Eds.; Zurich, 2014; pp. 185-194. ISBN 978-3-033-04515-6. Available online: http://www.morphologicalcomputation.org/e book/ (accessed on 6 December 2018). 50. Dempsey, L.P.; Shani, I. Stressing the Flesh: In Defense of Strong Embodied Cognition. Philos. Phenomenol. Res. 2013, 86, 590-617. [CrossRef] 51. Lungarella, M.; Sporns, O. Mapping Information Flow in Sensorimotor Networks. PLoS Comput. Biol. 2006, 2, e144. [CrossRef] [PubMed] 52. Caluwaerts, K.; Schrauwen, B. A Reservoir Computing View of Morphological Computation. In E-book on Opinions and Outlook on Morphological Computation; Hauser, H., Füchslin, R.M., Pfeifer, R., Eds.; 2014; pp. 25-38. Available online: http://www.morphologicalcomputation.org/e-book/ (accessed on 6 December 2018). 53. Lloyd, S. Universal Quantum Simulators. Science 1996, 273, 1073-1078. [CrossRef] [PubMed] 54. Papadimitriou, C.H. Computational Complexity; Addison-Wesley: Reading, MA, USA, 1993. 55. Van Rooij, I.; Wareham, T. Parameterized Complexity in Cognitive Modeling: Foundations, Applications and Opportunities. Comput. J. 2008, 51, 385-404. [CrossRef] 56. Feynman, R.P. Simulating physics with computers. Int. J. Theor. Phys. 1982, 21, 467-488. [CrossRef] 57. Deutsch, D. Quantum theory, the Church-Turing principle and the universal quantum computer. Proc. R. Soc. Lond. A 1985, 400, 97-117. [CrossRef] 58. Shor, P.W. Algorithms for quantum computation: discrete logarithms and factoring. In Proceedings of the 35th Annual Symposium on Foundations of Computer Science, Santa Fe, NM, USA, 20-22 November 1994; pp. 124-134. 59. Thornton, C. Gauging the value of good data: Informational embodiment quantification. Adapt. Behav. 2010, 18, 389-399. [CrossRef] 60. Friston, K. A Free Energy Principle for Biological Systems. Entropy 2012, 14, 2100-2121. 61. Colombo, M.; Wright, C. First principles in the life sciences: the free-energy principle, organicism, and mechanism. Synthese 2018, 1-26. [CrossRef] Entropy 2018, 20, 942 18 of 18 62. Friston, K.J. Embodied inference: Or “I think therefore I am, if I am what I think.” In The Implications of Embodiment (Cognition and Communication); Tschacher, W., Bergomi, C., Eds.; Imprint Academic: Exeter, UK, 2011; pp. 89-125. 63. Friston, K. Active inference and free energy. Behav. Brain Sci. 2013, 36, 212-213. [CrossRef] [PubMed] 64. Conant, R.C.; Ashby, W.R. Every good regulator of a system must be a model of that system. Int. J. Syst. Sci. 1970, 1, 89-97. [CrossRef] 65. Kaas, J.H.; Hackett, T.A. “What” and “where” processing in auditory cortex. Nat. Neurosci. 1999, 2, 1045-1047. [CrossRef] [PubMed] 66. Hall, D.A. Auditory Pathways: Are ‘Whatánd ‘Where' Appropriate? Curr. Biol. 2003, 13, R406-R408. [CrossRef] 67. Firestein, S. How the olfactory system makes sense of scents. Nature 2001, 413, 211-218. [CrossRef] [PubMed] 68. Pearl, J. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference; Morgan Kaufmann: San Francisco, CA, USA, 1988. 69. Eliasmith, C. A new perspective on representational problems. J. Cogn. Sci. 2005, 6, 97-123. 70. Arendt, D.; Tosches, M.A.; Marlow, H. From nerve net to nerve ring, nerve cord and brain—evolution of the nervous system. Nat. Rev. Neurosci. 2015, 17, 61-72. [CrossRef] 71. Pearl, J. Causality: Models, Reasoning, and Inference; Cambridge University Press: Cambridge, UK, 2000. © 2018 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 1. Pfeifer, R.; Iida, F. Morphological computation: Connecting body, brain and environment. Jpn. Sci. Mon. 2005, 58, 48-54. 2. Paul, C. Morphological computation: A basis for the analysis of morphology and control requirements. Robot. Auton. Syst. 2006, 54, 619-630.