The Semantic Shuffle: Shifting Emphasis in Dretske's Account of Representational Content

In Knowledge and the Flow of Information, Fred Dretske explains representational content by appealing to natural indication: a mental representation has its content in virtue of being a reliable natural indicator of a particular type of state of the world. His account fails for several reasons, not the least of which is that it cannot account for misrepresentation. Recognizing this, Dretske adds a twist in his more recent work on representational content (sketched in 'Misrepresentation' and elaborated in Explaining Behavior): a mental representation acquires its semantic content when the fact that it naturally indicates some type of state of the world acquires explanatory relevance. This shift in emphasis from natural indication to function (and, so, to behaviour) is intended to address the disjunction problem. Whether or not it succeeds (I argue that it does not), new problems emerge as a direct result of the shift to emphasis on behaviour. First, although Dretske appeals to appropriate response behaviours for particular types of representations, it is not at all clear that such behaviours exist. Second, Dretske's theory cannot account for representations that never figure in the behaviour of the organism of which they are a part. In response to these problems, I suggest two possible routes to recovery: one, an appeal to implicit beliefs (or dispositions); and, two, an appeal to compositionality. Although it seems clear that Dretske must enlist one of these options if he is to formulate a successful causal naturalist theory of representational content, given his theoretical commitments, neither option is readily available to him.     

Interpreting action as an answer

The aim of this paper is to introduce a logically grounded approach to action semantics and action interpretation. The main idea is to present the context of action as a set of questions demanding an action to answer. I introduce (a) a basic procedure of action interpretation, which is a reformulation of Hilpinen's semantical procedure for imperatives; (b) a procedure of what-interpretation; (c) a procedure of why-interpretation. The conditions of mutual reducibility of interpretation procedures are explicated. The paper concludes by putting forth the problem of interpretive bounds of moral responsibility.     

无穷探索与终极答案——从两个有神论兼无神论的小故事看科学与神学的区别

科学承认人类还有很多未知领域,神学才宣称所有问题皆已有答案。科学只给出目前可以验证的答案,对尚验证不了答案的问题继续进行探索;而神学则认为自己给出的是最终的答案,不需要继续探究。用了神学方法,任何动脑筋的事情都可以省了。     

Defining answer classes using resolution refutation

Resolution theorem proving provides a useful paradigm for the exploration of question answering. A partition of the clauses generated during resolution refutation based on their syntactic structure is presented. The three classes comprising this partition correspond to semantically intuitive types of answers. This work encompasses and expands upon previous work on question answering in a theorem proving paradigm, which began with the association of answers with proofs. A complete, formal definition of what is meant by answer in the context of resolution theorem proving is presented. In this context, clauses that are relevant are all identified as answers, where relevance is determined with respect to a question and knowledge base: any clause descended from the clause form of a negated question is deemed relevant. This definition of relevance is not in and of itself novel; rather, it is the way in which the set of relevant clauses is partitioned that provides the key to interpreting clauses as answers. The three answer classes identified are: specific, generic, and hypothetical. These classes are formally distinguished by the way in which literals in a clause share variables, with class membership based on a property termed the closure of variable sharing of a literal. The results presented provide a foundation for further work by establishing a context-independent logical pragmatics of question answering.     

Test theory without an answer key

A general model is presented for homogeneous, dichotomous items when the answer key is not known a priori. The model is structurally related to the two-class latent structure model with the roles of respondents and items interchanged. For very small sets of respondents, iterative maximum likelihood estimates of the parameters can be obtained by existing methods. For other situations, new estimation methods are developed and assessed with Monte Carlo data. The answer key can be accurately reconstructed with relatively small sets of respondents. The model is useful when a researcher wants to study objectively the knowledge possessed by members of a culturally coherent group that the researcher is not a member of.This research was supported by NSF Grant No. SES-8320173 to the authors. We gratefully acknowledge comments and suggestions from John Boyd, Tarow Indow, and Kathy Maher as well as the editor and several anonymous referees.     

Beyond the answer: post-error processes

When you suspect that you just gave an erroneous answer to a question you stop and rethink. Suspected errors lead to a shift in the control and content of cognitive processes. In the present experiment we investigated the influence of errors upon heart rates and response latencies. Sixty-four subjects participated in an experiment in which each subject solved a sequence of 60 verbal analogies. The results demonstrated increased latencies after errors and decelerated heart rates during the post-error period. The results were explained by a psychophysiological model in which the septo-hippocampal system functions as a control system which coordinates the priority and selection of cognitive processes. Error detection suppresses strategies which otherwise prevent looping and iterative reanalyses of old material. The inhibition is also responsible for the cardiac slowing during the post-error period.     

Open answer set programming for the semantic web

We extend answer set programming (ASP) with, possibly infinite, open domains. Since this leads to undecidable reasoning, we restrict the syntax of programs, while carefully guarding knowledge representation mechanisms such as negation as failure and inequalities. Reasoning with the resulting extended forest logic programs (EFoLPs) can be reduced to finite answer set programming, for which reasoners are available.We argue that extended forest logic programming is a useful tool for uniformly representing and reasoning with both ontological and rule-based knowledge, as they can capture a large fragment of the OWL DL ontology language equipped with DL-safe rules. Furthermore, EFoLPs enable nonmonotonic reasoning, a desirable feature in locally closed subareas of the Semantic Web.