This paper outlines the main assumptions of relevance theory (Sperber & Wilson 1985, 1995, 1998, 2002, Wilson & Sperber 2002), an inferential approach to pragmatics. Relevance theory is based on a definition of relevance and two principles of relevance: a Cognitive Principle (that human cognition is geared to the maximisation of relevance), and a Communicative Principle (that utterances create expectations of optimal relevance). We explain the motivation for these principles and illustrate their application to a variety of pragmatic problems. We end by considering the implications of this relevance-theoretic approach for the architecture of the mind. 1

Concepts are the elementary units of reason and linguistic meaning. They are conventional and relatively stable. As such, they must somehow be the result of neural activity in the brain. The questions are: Where? and How? A common philosophical position is that all concepts—even concepts about action and perception—are symbolic and abstract, and therefore must be implemented outside the brain’s sensory-motor system. We will argue against this position using (1) neuroscientific evidence; (2) results from neural computation; and (3) results about the nature of concepts from cognitive linguistics. We will propose that the sensory-motor system has the right kind of structure to characterise both sensory-motor and more abstract concepts. Central to this picture are the neural theory of language and the theory of cogs, according to which, brain structures in the sensory-motor regions are exploited to characterise the so-called “abstract ” concepts that constitute the meanings of grammatical constructions and general inference patterns.

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Metaphor comprehension involves an interaction between the meaning of the topic and vehicle terms of the metaphor. Meaning is represented by vectors in a high-dimensional semantic space. Predication modifies the topic vector by merging it with selected features of the vehicle vector. The resulting metaphor vector can be evaluated by comparing it with known landmarks in the semantic space. Thus, metaphorical predication is treated in the present model in exactly the same way as literal predication. Some experimental results concerning metaphor comprehension are simulated within this framework, such as the non-reversibility of metaphors, priming of metaphors with literal statements, and priming of literal statements with metaphors.

Current paradigms study language comprehension as if archival memory were its primary function. Subjects only receive linguistic material and are later tested on memory for its contents. In contrast, the two target articles in this issue, Glenberg and Robertson (in press) and Roth (in press), examine comprehension as if preparing for situated action were its primary function. Besides receiving linguistic materials as input, subjects study objects, actions, and interactions between agents. Rather than simply being tested on memory for linguistic materials, subjects also produce actions and enter into group interactions. Although these researchers focus their attention on specific genres---the comprehension of verbal instructions and the comprehension of scientific theories---their methods and findings have wider implications. In particular, the primary function of comprehension is not to archive information but is instead to prepare agents for situated action. Arguments from the evolution of cognition and language are brought to bear on this thesis, and perceptual simulation is proposed as a mechanism well-suited for supporting situated comprehension. Finally, it is conjectured that studying comprehension in the context of situated action is likely to produce significant scientific progress. Sense fades into reference. Roth (in press) If an outsider reviewed research on language comprehension, what conclusions might he or she reach? After reviewing this literature myself for a text on cognitive psychology (Barsalou, 1992, Chapters 8 and 9), I concluded that comprehension is essentially archival memory, describing it as follows: (1) Words enter the cognitive system through phonemic and graphemic processing. (2) Word representations are translated into amodal syntactic str...

Background noise is the irregular variation across repeated measurements of human performance. Background noise remains after task and treatment effects are minimized. Background noise refers to intrinsic sources of variability, the intrinsic dynamics of mind and body, and the internal workings of a living being. Two experiments demonstrate 1/f scaling (pink noise) in simple reaction times and speeded word naming times, which round out a catalog of laboratory task demonstrations that background noise is pink noise. Ubiquitous pink noise suggests processes of mind and body that change each other’s dynamics. Such interaction-dominant dynamics are found in systems that self-organize their behavior. Self-organization provides an unconventional perspective on cognition, but this perspective closely parallels a contemporary interdisciplinary view of living systems. Psychological science usually ignores the background noise in behavioral data. Background noise is what is left over when task demands, experimental manipulations, and other external sources of variability have been eliminated or minimized. What we call background noise is treated as random variability in most research, the nuisance factor in factorial experiments. We argue, to the

This paper is designed to illustrate and consider the relations between three types of metarepresentational ability used in verbal comprehension: the ability to metarepresent attributed thoughts, the ability to metarepresent attributed utterances, and the ability to metarepresent abstract, non-attributed representations (e.g. sentence types, utterance types, propositions). Aspects of these abilities have been separately considered in the literatures on “theory of mind”, Gricean pragmatics and quotation. The aim of this paper is to show how the results of these separate strands of research might be integrated with an empirically plausible pragmatic theory. 1

The article discusses claims that conceptual structure is in some part metaphorical, as identified by verbal metaphors like LOVE IS A JOURNEY. Two main interpretations of this view are discussed. In the first, a target domain is not explicitly represented but is instead understood through reference to a different domain. For example, rather than a detailed concept of love per se, one could make reference to the concept of a journey. In the second interpretation, there is a separate representation of love, but the content of that representation is influenced by the metaphor such that the love concept takes on the same structure as the journey concept. It is argued that the first interpretation is not fully coherent. The second interpretation is a possible theory of mental representation, but the article raises a number of empirical and theoretical problems for it. It is concluded that many of the data cited as evidence for metaphoric representations can be accounted for by structural similarity between domains. 1.

This thesis presents a computational framework for the automatic recognition and prediction of different kinds of human behaviors from video cameras and other sensors, via perceptually intelligent systems that automatically sense and correctly classify human behaviors, by means of Machine Perception and Machine Learning techniques. In the thesis I develop the statistical machine learning algorithms (dynamic graphical models) necessary for detecting and recognizing individual and interactive behaviors. In the case of the interactions two Hidden Markov Models (HMMs) are coupled in a novel architecture called Coupled Hidden Markov Models (CHMMs) that explicitly captures the interactions between them. The algorithms for learning the parameters from data as well as for doing inference with those models are developed and described. Four systems that experimentally evaluate the proposed paradigm are presented: (1) LAFTER, an automatic face detection and tracking system with facial expression recognition; (2) a Tai-Chi gesture recognition system; (3) a pedestrian surveillance system that recognizes typical human to human interactions; (4) and a SmartCar for driver maneuver recognition. These systems capture human behaviors of different nature and increasing complexity: first, isolated, single-user facial expressions, then, two-hand gestures and human-to-human interactions,...

This paper considers the implications for philosophy of some recent approaches to pragmatics (with a focus on relevance theory) and makes two main points. First, the widening gap between sentence meaning and speaker’s meaning increasingly brings into question a basic assumption of much philosophy of language: that linguistic semantics provides direct insight into the structure of human thoughts. Second, by describing comprehension as a richly context-dependent form of inference, pragmatics provides an illustration of how we might approach central cognitive processes, which have been seen by Fodor as a major mystery for cognitive psychology and philosophy of mind. 1