Perceptual experience has representational content. My argument for this claim is an inference to the best explanation. The explanandum is cognitive penetration. In cognitive penetration, perceptual experiences are either causally influenced, or else are partially constituted, by mental states that are representational, including: mental imagery, beliefs, concepts and memories. If perceptual experiences have representational content, then there is a background condition for cognitive penetration that renders the phenomenon prima facie intelligible. Naïve realist or purely relational accounts of perception leave cognitive (...) penetration less well-explained, even when formulated with so-called ‘standpoints’ or ‘third relata.’. (shrink)

Cases of past absence involve agents noticing in retrospect that an object or property was absent, such as when one notices later that a colleague was not at a talk. In Sanskrit philosophy, such cases are introduced by Kumārila as counterexamples to the claim that knowledge of absence is perceptual, but further take on a life of their own as a topic of inquiry among Kumārila’s commentators and their Nyāya interlocutors. In this essay, I examine the Nyāya philosopher Gaṅgeśa’s epistemology (...) of past absence, according to which agents learn that a recollectable object or property was absent by inferring its past absence from failing to recall that object or property. Gaṅgeśa’s account is best appreciated against the backdrop of earlier theories and their shortcomings, and I begin by presenting historical views leading up to his. I identify two groups of views about the epistemology of past absence: recollection views, according to which cases of past absence involve agents recalling negative information; and recollection failure views, according to which cases of past absence involve agents failing to recall positive information. I reconstruct two early recollection views: a Bhāṭṭa view belonging to Uṃveka, and a competing Nyāya view belonging to Jayanta and Bhāsarvajña. I then examine Śālikanātha and Sucarita’s critiques of recollection views, following which I reconstruct a Bhāṭṭa recollection failure view belonging to Pārthasārathi. I then examine Gaṅgeśa’s critiques of Pārthasārathi’s account and the recollection failure view he constructs out of its shortcomings. (shrink)

In this paper, we consider how certain longstanding philosophical questions about mental representation may be answered on the assumption that cognitive and perceptual systems implement hierarchical generative models, such as those discussed within the prediction error minimization framework. We build on existing treatments of representation via structural resemblance, such as those in Gładziejewski :559–582, 2016) and Gładziejewski and Miłkowski, to argue for a representationalist interpretation of the PEM framework. We further motivate the proposed approach to content by arguing that it (...) is consistent with approaches implicit in theories of unsupervised learning in neural networks. In the course of this discussion, we argue that the structural representation proposal, properly understood, has more in common with functional-role than with causal/informational or teleosemantic theories. In the remainder of the paper, we describe the PEM framework for approximate Bayesian inference in some detail, and discuss how structural representations might arise within the proposed Bayesian hierarchies. After explicating the notion of variational inference, we define a subjectively accessible measure of misrepresentation for hierarchical Bayesian networks by appeal to the Kullbach–Leibler divergence between posterior generative and approximate recognition densities, and discuss a related measure of objective misrepresentation in terms of correspondence with the facts. (shrink)