![]() |
![]() |
University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > Anticipatory Representational Mechanisms in Animals
Anticipatory Representational Mechanisms in AnimalsAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Leandro Minku. Host: Prof. Aaron Sloman, Note: unusual time and place Some of animal behavior can be explained by appeal to their internal or mental representations. For example, it is usually agreed that rats are capable of path integration (even in complete darkness, and when immersed in a water maze) because they maintain a cognitive map of their environment. Exactly how and why neural states give rise to mental representations is a matter of an ongoing debate. The purpose of my talk is to show that anticipatory mechanisms involved in rats’ cognitive maps meet Ramsey’s (2007) “job description challenge”: it is clear in what way they are representationally relevant for explaining and predicting rats behavior. First, I introduce the idea of anticipatory representational mechanisms, which is used to analyze the current research in ethology, cognitive science, and neuroscience. Representational mechanisms (Mi?kowski, 2013) have at least the following capacities: (a) referring to the target (if any) of the representation; (b) identifying the characteristics target; (c) evaluating the epistemic value of information about the target. While the first two capacities bear close resemblance to traditional notions of extension and intension, the third one is supposed to link the representational mechanism with the work of the agent or system that peruses it. Such mechanisms are representational in that that they enable the system to detect that it is in error (via evaluation of the epistemic value) and they are prone to misidentification of targets because of the referential opacity. Both aspects, namely system-detectable error and referential opacity, are the basis for the causal relevance of content in representational mechanisms. The anticipatory representational mechanisms have an additional capacity to anticipate the future characteristics of the represented target. Anticipatory capacities are posited widely in current cognitive science (Pezzulo, 2008, 2011) and they have deep connections with Rosen’s anticipatory systems (Rosen, 1991, 2012). I will claim that anticipatory mechanisms in my sense meet Ramsey’s challenge, and that taxis behavior in animals does not. This suggests that the presence of anticipation is also strong evidence for the presence of representation in observed animals. In particular, the role of error detection (for which there is partial neurological evidence in rats) will be stressed. References: Milkowski, M. (2013). Explaining the Computational Mind. Cambridge, Mass.: MIT Press. Pezzulo, G. (2008). Coordinating with the Future: The Anticipatory Nature of Representation. Minds and Machines, 18(2), 179-225. doi:10.1007/s11023-008-9095-5 Pezzulo, G. (2011). Grounding Procedural and Declarative Knowledge in Sensorimotor Anticipation. Mind & Language, 26(1), 78-114. doi:10.1111/j.1468-0017.2010.01411.x Ramsey, W. M. (2007). Representation Reconsidered. Cambridge: Cambridge University Press. doi:10.1017/CBO9780511597954 Rosen, R. (1991). Life itself: a comprehensive inquiry into the nature, origin, and fabrication of life. New York: Columbia University Press. Rosen, R. (2012). Anticipatory systems: philosophical, mathematical, and methodological foundations (2nd ed.). New York: Springer. Speaker’s homepage: http://marcinmilkowski.pl/en/ This talk is part of the Artificial Intelligence and Natural Computation seminars series. This talk is included in these lists:
Note that ex-directory lists are not shown. |
Other listsAstrophysics Talks Series Analysis seminar School of Chemistry SeminarsOther talksSeminar: TBA Spectrally selective metasurfaces based on bound states in the continuum: a versatile platform for enhanced light-matter coupling Cost optimisation of hybrid institutional incentives for promoting cooperation in finite populations Geometry of alternating projections in metric spaces with bounded curvature Modelling uncertainty in image analysis. Colloquium: TBA |