References
- Allen, C., & Bekoff, M. (1997). Species of mind: The philosophy and biology of cognitive ethology. Cambridge, MA: MIT Press.
- Anderson, D., & Perona, P. (2004). Toward a science of computational ethol- ogy. Neuron, 1, 18–31.
- Bajcsy, R., Aloimonos, Y., & Tsotsos, J. K. (2018). Revisiting active perception. Autonomous Robots, 42, 177–196.
- Beauchamp, G. (2003). Group-size effects on vigilance: A search for mech- anisms. Behavioural Processes, 63(111–121), 111–121.
- Beauchamp, G. (2017). Disentangling the various mechanisms that account for the decline in vigilance with group size. Behavioural Processes, 136, 59–63.
- Bekey, G. A. (2005). Autonomous Robots: From biological inspiration to imple- mentation and control. Cambridge, MA: MIT Press.
- Bickle, J. (2008). Real reduction in real neuroscience: Metascience, not philosophy of science (and certainly not metaphysics!). In J. Howhy & J. Kallestrup (Eds.), Being reduced: New essays on reduction, explanation, and causation (pp. 34–51). Oxford, UK: Oxford University Press.
- Bickle, J., & Silva, A. (2009). Science of research and the search for the molecular mechanisms of cognitive functions. In J. Bickle (Ed.), Oxford handbook of philosophy and neuroscience (pp. 71–126). Oxford, UK: Oxford University Press.
- Brentano, F. (1874). Psychology from an Empirical Standpoint. London: Routledge.
- Burge, T. (2010). Origins of objectivity. Oxford, UK: Oxford University Press.
- Carrasco, M. (2011). Visual attention: The past 25 years. Vision Research, 51, 1484–1525.
- Chalmers, D. (2011). A computational foundation for the study of cogni- tion. Journal of Cognitive Science, 12(4), 323–357.
- Clark, A. (2008). Supersizing the Mind: Embodiment, action, and cognitive extension. New York: Oxford University Press.
- Cowan, N. J., Ankarali, M. M., Dyhr, J. P., Madhav, M. S., Roth, E., Sefati, S., … Daniel, T. L. (2014). Feedback control as a framework for understanding tradeoffs in biology. Integrative and Comparative Biology, 54(2), 223–237.
- Craver, C. F. (2007). Explaining the Brain: Mechanisms and the mosaic unity of neuroscience. Oxford, UK: Oxford University Press.
- Davenport, D. (2012). Computationalism: Still the only game in town. Minds and Machines, 22(3), 183–190.
- Der, R., & Martius, G. (2017). Self-organized behavior generation for mus- culoskeletal robots. Frontiers in Neurorobotics, 11(8).
- Dreyfus, H. (1972). What computers can’t do: A critique of artificial reason. New York, NY: Harper and Row.
- Dreyfus, H. (1992). What computers still can’t do: A critique of artificial reason. Cambridge, MA: MIT Press.
- Egan, F. (2014). How to think about mental content. Philosophical Studies, 170(1), 115–135.
- Erdmann, M. (2010). On the topology of discrete strategies. The Interna- Tional Journal of Robotics Research, 29(7), 855–896.
- Fodor, J. (1975). The language of thought. Cambridge, MA: Harvard University Press.
- Fodor, J. (1987). Psychosemantics. Cambridge, MA: MIT Press.
- Fodor, J. (2000). The mind doesn’t work that way: The scope and limits of computational psychology. Cambridge, MA: MIT Press.
- Gebharter, A. (2015). Causal exclusion and causal bayes nets. Philosophy and Phenomenological Research. doi:10.1111/phpr.12247
- Gebharter, A. (2016). Uncovering constitutive relevance relations in mech- anisms. Philosophical Studies. doi:10.1007/s11098–016–0803–3
- Gibson, J. J. (1979). The ecological approach to visual perception. Boston: Houghton-Mifflin.
- Godrey-Smith, P. (2008). Reduction in real life. In J. Howhy & J. Kallestrup (Eds.), Being reduced: New essays on reduction, explanation, and causation. Cambridge, UK: Oxford University Press.
- Griffiths, P., & Stotz, K. (2013). Genetics and philosophy: An introduction. Cambridge University Press.
- HáJek, A. (2007). The reference class problem is your problem too. Synthese, 156, 185–215.
- Halpern, J. Y., & Pearl, J. (2001a). Causes and explanations: A structural- model approach—Part 2: Explanations. Technical report R-266-IJCAI, UCLA cognitive systems laboratory (pp. 2001). San Francisco, CA: Morgan Kauf- mann.
- Halpern, J. Y., & Pearl, J. (2001b). Causes and explanations: A structural- model approach—Part i: Causes. Technical Report R-266-UAI UCLA Cognitive Systems Laboratory.
- Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017). Neuroscience-inspired artificial intelligence. Neuron, 95(2), 245–258.
- Hassabis, D., & Maguire, E. A. (2007). Deconstructing episodic memory with construction. Trends in Cognitive Sciences, 11(7), 299–306.
- Hassabis, D., & Maguire, E. A. (2009). The construction system of the brain. Philosophical Transactions of the Royal Society of London, B Divison (Bio- Logical Sciences), 364, 1263–1271.
- Haugeland, J. (1978). The nature and plausibility of cognitivism. Behavioral and Brain Sciences, 1(2), 215–260.
- Hawley, K. (2003). Success and knoweldge how. American Philosophical Quarterly, 40(1), 19–31.
- Hempel, C. (1965). Aspects of Scientific Explanation. New York, NY: Free Press.
- Hirsch, M. W., Smale, S., & Devaney, R. L. (2004). Differential equations, dynamical systems, and an introduction to chaos. Waltham, MA: Elsevier.
- Hitchcock, C. (2001). The intransitivity of causation revealed in equations and graphs. Journal of Philosophy, 98(6), 273–299.
- Hitchcock, C. (2007). Prevention, preemption, and the principle of suffi- cient reason. Philosophical Review, 116(4), 495–532.
- Johnson, A. M., Burden, S. A., & Koditschek, D. E. (2016). A hybrid systems model for simple manipulation and self-manipulation systems. The Interna- Tional Journal of Robotics Research, 35(11), 1354–1392.
- Kagaya, K., & Takahata, M. (2010). Readiness discharge for spontaneous initiation of walking in crayfish. The Journal of Neuroscience, 30(4), 1348–1362.
- Keeley, B. L. (2004). Anthropomorphism, primatomorphism, mammalo- morphism: Understanding cross-species comparisons. Biology and Phi- Losophy, 19, 521–540.
- Khatib, O. (1986). Real-time obstacle avoidance for manipulators and mo- bile robots. The International Journal of Robotics Research, 5(1), 90–98.
- Klein, C. (2017). Brain regions as difference makers. Philosophical Psychology, 30(1–2), 1–20.
- Koditschek, D. E. (1987). Quadratic lyapunov functions for mechanical systems. Technical report. Yale University, Center for Systems Science.
- Koditschek, D. E. (1992). Task encoding: Toward a scientific paradigm for robot planning and control. Robotics and autonomous systems.
- Kowler, E. (2011). Eye movements: The past 25 years. Vision Research, 51, 1457–1483.
- Krakauer, J. W., Ghazanfar, A. A., Gomez-Marin, A., MacIver, M. A., & Poeppel, D. (2017). Neuroscience needs behavior: Correcting a reduc- tionist bias. Neuron, 93(3), 480–490.
- Larochelle, H., & Hinton, G. (2010). Learning to combine foveal glimpses with a third-order boltzmann machine. In NIPS’10 Proceedings of the International Conference on Neural Information Processing Systems (pp. 1243–1251). https://papers.nips.cc/
- Lee, C.-S., Wang, M.-H., Yen, S.-J., Wei, T.-H., Wu, I.-C., Chou, P.-C., … Yan, T.-H. (2016). Human vs. computer go: Review and prospect. IEEE Computational Intelligence Magazine, 11(3), 67–72.
- Lewis, D. (1973). Causation. Journal of Philosophy, 70, 556–567.
- Libet, B., Gleason, C., Wright, E., & Pearl, D. (1983). Time of conscious intention to act in relation to onset of cerebral activity (readiness- potential): The unconscious initiation of a freely voluntary act. Brain, 106, 623–642.
- Marr, D. (1982). Vision: A computational investigation into the human representation and processing of visual information. San Francisco, CA: W.H. Freeman and Company.
- Marr, D., & Poggio, T. (1976). From understanding computation to under- sanding neural circuitry. A.I. Memo 357, Massachusetts Institute of Technology, Artificial Intelligence Laboratory.
- McCarthy, J., & Hayes, P. J. (1969). Some philosophical problems from the standpoint of artificial intelligence. In D. M. B. Meltzer & M. Swann (Eds.), Machine Intelligence 4 (pp. 463–502). Edinburgh: Edinburgh Uni- versity Press.
- McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation model of context effects in letter perception: Part 1. An account of basic findings. Psychological Review, 88(5), 375–407.
- McClelland, J. L., & Rumelhart, D. E. (1986). Parallel distributed processing: Explorations in the microstructure of cognition: Foundations, volume 1. Cambridge, MA: MIT Press.
- McCulloch, W. S., & Pitts, W. (1943). A logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biophysics, 7, 115–133.
- Minsky, M. (1986). The society of mind. New York, NY: Simon & Schuster.
- Miracchi, L. (2015). Competence to know. Philosophical Studies, 172(1), 29–56.
- Miracchi, L. (2017a). Generative explanation in cognitive science and the hard problem of consciousness. Philosophical Perspectives, 31, 267–291.
- Miracchi, L. (2017b). Perception first. Journal of Philosophy, 114(12), 629–677.
- Miracchi, L. (forthcoming). Competent perspectives and the new evil demon problem. In F. Dorsch & J. Dutant (Eds.), The new evil demon: New essays on knowledge, justification and rationality. Oxford University Press.
- Mnih, V., Heess, N., Graves, A., & Kavukcuoglu, K. (2014). Recurrent models of visual attention. arXiv, arXiv:14066247.
- Nagel, T. (1974). What is it like to be a bat?. Philosophical Review, 83, 435–450.
- Pais, D., Hogan, P. M., Schlegel, T., Franks, N. R., Leonard, N. E., & Marshall, J. A. R. (2013). A mechanism for value-sensitive decision-making. PLOS ONE, 8, 1–9.
- Palmer, S. E. (1999). Vision science: From photons to phenomenology. Cambridge, MA: MIT Press.
- Peacocke, C. (1994). Content, computation, and externalism. Mind and Language, 9(3), 303–335.
- Pearl, J. (2000). Causality: Models, reasoning and inference. Cambridge, UK: Cambridge University Press.
- Putnam, H. (1967). The nature of mental states. In Reprinted in: The philosophy of mind: Classical problems/ contemporary issues (1992) (pp. 51–58). Cambridge, MA: MIT Press.
- Raghu, M., Gilmer, J., Yosinski, J., & Sohl-Dickstein, J. (2017). Svcca: Sin- gular vector canonical correlation analysis for deep learning dynamics and interpretability. arXiv, (1706.05806v2).
- Rescorla, M. (2014). The causal relevance of content to computation. Philosophy and Phenomenological Research, 88(1), 173–208.
- Reverdy, P., & Koditschek, D. E. (2018). A dynamical system for prioritizing and coordinating motivations. SIAM Journal on Applied Dynamical Systems, 17(2), 1683–1715.
- Rimon, E., & Koditschek, D. E. (1992). Exact robot navigation using artificial potential functions. IEEE Transactions on Robotics and Automation, 8(5), 501–518.
- Rumelhart, D. E., & McClelland, J. L. (1982). An interactive activation model of context effects in letter perception: Part 2. The contextual en- hancement effect and some tests and extensions of theh model. Psycho- Logical Review, 89(1), 60–94.
- Russell, S., & Norvig, P. (2014). Artificial intelligence: A modern approach. ( 3rd). Upper Saddle River, NJ: Prentice-Hall.
- Schoner, G., Does, M., & Engels, C. (1995). Dynamics of behavior: The- ory and applications for autonomous robot architectures. Robotics and Autonomous Systems, 16, 213–245.
- Schurger, A., Sitt, J. D., & Dehaene, S. (2012). An accumulator model for spontaneous neural activity prior to self-initiated movement. Proceedings of the National Academy of Sciences, 109(42), E2904–E2913.
- Schurger, A., & Uithol, S. (2015). Nowhere and everywhere: The causal origin of voluntary action. Review of Philosophy and Psychology, 6, 761–778.
- Searle, J. (1984). Minds, brains, and science. Cambridge, MA: Harvard University Press.
- Setiya, K. (2012). Knowing how. Proceedings of the Aristotelian Society, 112(3.3), 285–307.
- Silver, D., & Huang, A. (2016). Mastering the game of go with deep neural networks and tree search. Nature, 529(7587), 484–489.
- Smolensky, P. (1991). Connectionism, constituency, and the language of thought. In B. M. Loewer & G. Rey (Eds.), Meaning in mind: Fodor and his critics. Cambridge, MA: Blackwell.
- Sosa, E. (2007). A virtue epistemology: Apt belief and reflective knowledge, volume 1. Oxford, UK: Oxford University Press.
- Sosa, E. (2015). Judgment and Agency. Cambridge, MA: Oxford University Press.
- Spirtes, P., Glymour, C., & Scheines, R. (2000). Causation, prediction and search (2nd ed.). Cambridge, MA: MIT Press.
- Strevens, M. (2004). The causal and unification approaches to explanation unified—Causally. Noûs, 38(1), 154–176.
- Strevens, M. (2008). Depth. Cambridge, MA: Harvard University Press.
- Sutton, E. E., Demir, A., Stamper, S. A., Fortune, E. S., & Cowan, N. J. (2016). Dynamic modulation of visual and electrosensory gains for mo- tor control. Journal of the Royal Society Interface, 13(20160057).
- Woodward, J. (2003). Making Things Happen. Oxford, UK: Oxford University Press.
- Woodward, J. (2008). Mental causation and neural mechanisms. In J. Hohwy & J. Kallestrup (Eds.), Being reduced: New essays on reduction, explanation, and causation. Oxford, UK: Oxford University Press.