Robert Cummins

What are the prospects for a cognitive science of meaning? As stated, we think this question is ill posed, for it invites the conflation of several importantly different semantic concepts. In this paper, we want to distinguish the sort of meaning that is an explanandum for cognitive science—something we are going to call meaning—from the sort of meaning that is an explanans in cognitive science—something we are not going to call meaning at all, but rather content. What we are going to call meaning is paradigmatically a property of linguistic expressions or acts: what one’s utterance or sentence means, and what one means by it. What we are going to call content is a property of, among other things, mental representations and indicator signals. We will argue that it is a mistake to identify meaning with content, and that, once this is appreciated, some serious problems emerge for grounding meaning in the sorts of content that cognitive science is likely to provide.

In book two, Chapter eight of the essay, Locke claims that primary qualities, Unlike secondary qualities, Are really in objects and are resemblances of our ideas. The idioms of containment and of resemblance are explained as formulations of what jonathan bennett calls the analytic thesis and the causal thesis. It is argued that locke was concerned to distinguish primary qualities from what he calls secondary qualities because he thought the latter were not really qualities at all but mere powers and hence not genuinely explanatory.

The Knowledge Argument of Frank Jackson has not persuaded physicalists, but their replies have not dispelled the intuition that someone raised in a black and white environment gains genuinely new knowledge when she sees colors for the first time. In what follows, we propose an explanation of this particular kind of knowledge gain that displays it as genuinely new, but orthogonal to both physicalism and phenomenology. We argue that Mary’s case is an instance of a common phenomenon in which something new is learned as the result of exploiting representational resources that were not previously exploited, and that this results in gaining genuinely new information.

I've tried to argue that there is more to representational content than CRS can acknowledge. CRS is attractive, I think, because of its rejection of atomism, and because it is a plausible theory of targets. But those are philosopher's concerns. Someone interested in building a person needs to understand representation, because, as AI researchers have urged for some time, good representation is the secret of good performance. I have just gestured in the direction I think a viable theory of representation must take. I hope, however, to have created some advance sympathy for the gesture by distinguishing the problem of representation from the problem of targets on the one hand, and from the problem truth-conditions for the attitudes on the other.

It has been commonplace in epistemology since its inception to idealize away from computational resource constraints, i.e., from the constraints of time and memory. One thought is that a kind of ideal rationality can be specified that ignores the constraints imposed by limited time and memory, and that actual cognitive performance can be seen as an interaction between the norms of ideal rationality and the practicalities of time and memory limitations. But a cornerstone of naturalistic epistemology is that normative assessment is constrained by capacities: you cannot require someone to do something they cannot or, as it is usually put, ought implies can. This much we take to be uncontroversial. We argue that differences in architectures, goals and resources imply substantial differences in capacity, and that some of these differences are ineliminable. It follows that some differences in goals and architectural and computational resources matter at the normative level: they constrain what principles of normative epistemology can be used to describe and prescribe their behavior. As a result, we can expect there to be important epistemic differences between the way brains, individuals, and science work.

The background hypothesis of this essay is that psychological phenomena are typically explained, not by subsuming them under psychological laws, but by functional analysis. Causal subsumption is an appropriate strategy for explaining changes of state, but not for explaining capacities, and it is capacities that are the central explananda of psychology. The contrast between functional analysis and causal subsumption is illustrated, and the background hypothesis supported, by a critical reassessment of the motivational psychology of Clark Hull. I argue that Hull's work makes little sense construed along the subsumptivist lines he advocated himself, but emerges as both interesting and methodologically sound when construed as an exercise in the sort of functional analysis featured in contemporary cognitive science.

The purpose of this paper is to set forth a sense in which programs can and do explain behavior, and to distinguish from this a number of senses in which they do not. Once we are tolerably clear concerning the sort of explanatory strategy being employed, two rather interesting facts emerge; (1) though it is true that programs are "internally represented," this fact has no explanatory interest beyond the mere fact that the program is executed; (2) programs which are couched in information processing terms may have an explanatory interest for a given range of behavior which is independent of physiological explanations of the same range of behavior.

It is commonly supposed that evolutionary explanations of cognitive phenomena involve the assumption that the capacities to be explained are both innate and modular. This is understandable: independent selection of a trait requires that it be both heritable and largely decoupled from other ”nearby’ traits. Cognitive capacities realized as innate modules would certainly satisfy these contraints. A viable evolutionary cognitive psychology, however, requires neither extreme nativism nor modularity, though it is consistent with both. In this paper, we seek to show that rather weak assumptions about innateness and modularity are consistent with evolutionary explanations of cognitive capacities. Evolutionary pressures can affect the degree to which the development of a capacity is canalized by biasing acquisition/learning in ways that favor development of concepts and capacities that proved adaptive to an organism’s ancestors.

In this paper, I sketch a revision of jonathan bennett's "meaning-Nominalist strategy" for explaining the conventional meanings of utterance-Types. Bennett's strategy does not explain sentence-Meaning by appeal to sub-Sentential meanings, And hence cannot hope to yield a theory that assigns a meaning to every sentence. I revise the strategy to make it applicable to predication and identification. The meaning-Convention for a term can then be used to fix its satisfaction conditions. Adapting a familiar trick of tarski's, We can then determine an infinity of conventional meanings from a finite number of meaning-Conventions.