Semantic composition in language must be closely related to semantic composition in thought. But the way the two processes are explained differs considerably. Focusing primarily on propositional content, language theorists generally take semantic composition to be a truth‐conditional process. Focusing more on extensional content, cognitive theorists take it to be a form of concept combination. But though deep, this disconnect is not irreconcilable. Both areas of theory assume that extensional (i.e., denotational) meanings must play a role. As this article demonstrates, (...) they also have the potential to fulfill a mediative function. What is shown is that extensional meanings are themselves inherently compositional. On this basis, it becomes possible to model semantic composition without assuming the existence of any specifically linguistic/conceptual apparatus. Examples are presented to demonstrate this direct style of modeling. Abstract connections between composition in thought and language can then be made, raising the prospect of a more unified, theoretical account of semantic composition. (shrink)

“Force dynamics” refers to a previously neglected semantic category—how entities interact with respect to force. This category includes such concepts as: the exertion of force, resistance to such exertion and the overcoming of such resistance, blockage of a force and the removal of such blockage, and so forth. Force dynamics is a generalization over the traditional linguistic notion of “causative”: it analyzes “causing” into finer primitives and sets it naturally within a framework that also includes “letting,”“hindering,”“helping,” and still further notions. (...) Force dynamics, moreover, appears to be the semantic category that uniquely characterizes the grammatical category of modals, in both their basic and epistemic usages. In addition, on the basis of force dynamic parameters, numerous lexical items fall into systematic semantic patterns, and there exhibit parallelisms between physical and psychosocial reference. Further, from research on the relation of semantic structure to general cognitive structure, it appears that the concepts of force interaction that are encoded within language closely parallel concepts that appear both in early science and in naive physics and psychology. Overall, force dynamics thus emerges as a fundamental notional system that structures conceptual material pertaining to force interaction in a common way across a linguistic range: the physical, psychological, social, inferential, discourse, and mental‐model domains of reference and conception. (shrink)

Cognitive ecology is the study of cognitive phenomena in context. In particular, it points to the web of mutual dependence among the elements of a cognitive ecosystem. At least three fields were taking a deeply ecological approach to cognition 30 years ago: Gibson’s ecological psychology, Bateson’s ecology of mind, and Soviet cultural-historical activity theory. The ideas developed in those projects have now found a place in modern views of embodied, situated, distributed cognition. As cognitive theory continues to shift from units (...) of analysis defined by inherent properties of the elements to units defined in terms of dynamic patterns of correlation across elements, the study of cognitive ecosystems will become an increasingly important part of cognitive science. (shrink)

This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...) e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation. (shrink)

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity (...) producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporateeverything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments. (shrink)

Lectures on Perception: An Ecological Perspective addresses the generic principles by which each and every kind of life form--from single celled organisms to multi-celled organisms --perceives the circumstances of their living so that they can behave adaptively. It focuses on the fundamental ability that relates each and every organism to its surroundings, namely, the ability to perceive things in the sense of how to get about among them and what to do, or not to do, with them. The book's core (...) thesis breaks from the conventional interpretation of perception as a form of abduction based on innate hypotheses and acquired knowledge, and from the historical scientific focus on the perceptual abilities of animals, most especially those abilities ascribed to humankind. Specifically, it advances the thesis of perception as a matter of laws and principles at nature's ecological scale, and gives equal theoretical consideration to the perceptual achievements of all of the classically defined 'kingdoms' of organisms--Archaea, Bacteria, Protoctista, Fungi, Plantae, and Animalia. (shrink)

This article mentions that a formal view of compositional semantics is helpful both for what it reveals about the structure of language and also for what it deletes, including context, the use of compositionality to index rather than define meaning, and the role of idioms. It also discusses how Construction Grammar allows one to incorporate idioms into a framework in which compositionality may sometimes use familiar sequences of words as atoms when the meanings of single words do not themselves contribute (...) to the meaning of the whole. Schema Theory shows what is meant by embodied meaning, and the way it is embedded in social experience. Linguists working within CG, with its close relations to Cognitive Grammar, have teased out the rule-governed and productive linguistic behaviors specific to each family of constructions. (shrink)

Abstract“Force dynamics” refers to a previously neglected semantic category—how entities interact with respect to force. This category includes such concepts as: the exertion of force, resistance to such exertion and the overcoming of such resistance, blockage of a force and the removal of such blockage, and so forth. Force dynamics is a generalization over the traditional linguistic notion of “causative”: it analyzes “causing” into finer primitives and sets it naturally within a framework that also includes “letting,”“hindering,”“helping,” and still further notions. (...) Force dynamics, moreover, appears to be the semantic category that uniquely characterizes the grammatical category of modals, in both their basic and epistemic usages. In addition, on the basis of force dynamic parameters, numerous lexical items fall into systematic semantic patterns, and there exhibit parallelisms between physical and psychosocial reference. Further, from research on the relation of semantic structure to general cognitive structure, it appears that the concepts of force interaction that are encoded within language closely parallel concepts that appear both in early science and in naive physics and psychology. Overall, force dynamics thus emerges as a fundamental notional system that structures conceptual material pertaining to force interaction in a common way across a linguistic range: the physical, psychological, social, inferential, discourse, and mental-model domains of reference and conception. (shrink)

The aim of the article is to present a model of causal relations that is based on what is known about human causal reasoning and that forms guidelines for implementations in robots. I argue for two theses concerning human cognition. The first is that human causal cognition, in contrast to that of other animals, is based on the understanding of the forces that are involved. The second thesis is that humans think about causality in terms of events. I present a (...) two-vector model of events, developed by Gärdenfors and Warglien, which states that an event is represented in terms of two main components – the force of an action that drives the event, and the result of its application. Apart from the causal mapping, the event model contains representations of a patient, an agent, and possibly some other roles. Agents and patients are objects (animate or inanimate) that have different properties. Following my theory of conceptual spaces, they can be described as vectors of property values. At least two spaces are needed to describe an event, an action space and a result space. The result of an event is modeled as a vector representing the change of properties of the patient before and after the event. In robotics the focus has been on describing results. The proposed model also includes the causal part of events, typically described as an action. A central part of an event category is the mapping from actions to results. This mapping contains the central information about causal relations. In applications of the two-vector model, the central problem is how the event mapping can be learned in a way that is amenable to implementations in robots. Three processes are central for event cognition: causal thinking, control of action and learning by generalization. Although it is not yet clear which is the best way to model how the mappings can be learned, they should be constrained by three corresponding mathematical properties: monotonicity (related to qualitative causal thinking); continuity (plays a key role in activities of action control); and convexity (facilitates generalization and the categorization of events). I argue that Bayesian models are not suitable for these purposes, but some more geometrically oriented approach to event mappings should be used. (shrink)

Cognitive Science, Volume 46, Issue 7, July 2022.