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  1. Informational Theories of Content and Mental Representation.Marc Artiga & Miguel Ángel Sebastián - 2020 - Review of Philosophy and Psychology 11 (3):613-627.
    Informational theories of semantic content have been recently gaining prominence in the debate on the notion of mental representation. In this paper we examine new-wave informational theories which have a special focus on cognitive science. In particular, we argue that these theories face four important difficulties: they do not fully solve the problem of error, fall prey to the wrong distality attribution problem, have serious difficulties accounting for ambiguous and redundant representations and fail to deliver a metasemantic theory of representation. (...)
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  • Information as a Probabilistic Difference Maker.Andrea Scarantino - 2015 - Australasian Journal of Philosophy 93 (3):419-443.
    By virtue of what do alarm calls and facial expressions carry natural information? The answer I defend in this paper is that they carry natural information by virtue of changing the probabilities of various states of affairs, relative to background data. The Probabilistic Difference Maker Theory of natural information that I introduce here is inspired by Dretske's [1981] seminal analysis of natural information, but parts ways with it by eschewing the requirements that information transmission must be nomically underwritten, mind-independent, and (...)
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  • Prospects for Probabilistic Theories of Natural Information.Ulrich E. Stegmann - 2015 - Erkenntnis 80 (4):869-893.
    Much recent work on natural information has focused on probabilistic theories, which construe natural information as a matter of probabilistic relations between events or states. This paper assesses three variants of probabilistic theories (due to Millikan, Shea, and Scarantino and Piccinini). I distinguish between probabilistic theories as (1) attempts to reveal why probabilistic relations are important for human and non-human animals and as (2) explications of the information concept(s) employed in the sciences. I argue that the strength of probabilistic theories (...)
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