This article presents two learning processes in order to explain how children at an early age can transform a complex sensory input to concepts and categories. The first process constructs the perceptual structures that emerge in children’s cognitive development by detecting invariants in the sensory input. The invariant structures involve a reduction in dimensionality of the sensory information. It is argued that this process generates the primary domains of space, objects and actions and that these domains can be represented as (...) conceptual spaces. Once the primary domains have been established, the second process utilizes covariances between different dimensions of the domains in order to identify natural clusters of entities. The clusters are then are used to determine concepts as regions in the spaces. As an application, the processes are used to resolve the so-called ‘complex first paradox’ that emerges from the fact that children, in general, learn nouns earlier than adjectives, even though nouns are semantically more complex than adjectives. (shrink)

This paper offers a modeling account of episodic representation. I argue that the episodic system constructsmental models: representations that preserve the spatiotemporal structure of represented domains. In prototypical cases, these domains are events: occurrences taken by subjects to have characteristic structures, dynamics and relatively determinate beginnings and ends. Due to their simplicity and manipulability, mental event models can be used in a variety of cognitive contexts: in remembering the personal past, but also in future-oriented and counterfactual imagination. As structural representations, (...) they allow surrogative reasoning, supporting inferences about their constituents which can be used in reasoning about the represented events. (shrink)

Events can be modeled through a geometric approach, representing event structures in terms of spaces and mappings between spaces. At least two spaces are needed to describe an event, an action space and a result space. In this article, we invoke general mathematical structures in order to develop this geometric perspective. We focus on three cognitive processes that are crucially involved in events: causal thinking, control of action and learning by generalization. These cognitive processes are supported by three corresponding mathematical (...) properties: monotonicity (that we relate to qualitative causal thinking and allows extrapolation); continuity (that plays a key role in our activities of action control); and convexity (that facilitates generalization and the categorization of events, and enables interpolation). We define how such properties constrain events representations and relate them to thinking about events. We discuss the relevance of the three constraints for event segmentation and explore the implications of such constraints for semantics. We conclude by a discussion that relates our approach to other accounts of events. (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)

The world as we perceive it is structured into objects, actions and places that form parts of events. In this article, my aim is to explain why these categories are cognitively primary. From an empiricist and evolutionary standpoint, it is argued that the reduction of the complexity of sensory signals is based on the brain's capacity to identify various types of invariances that are evolutionarily relevant for the activities of the organism. The first aim of the article is to explain (...) why places, object and actions are primary cognitive categories in our constructions of the external world. It is shown that the invariances that determine these categories have their separate characteristics and that they are, by and large, independent of each other. This separation is supported by what is known about the neural mechanisms. The second aim is to show that the category of events can be analyzed as being constituted of the primary categories. The category of numbers is briefly discussed. Some implications for computational models of the categories are also presented. (shrink)

In this article, I introduce a semiosic translation of Wittgenstein’s Tractatus Logico-Philosophicus. The theoretical framework is Semiosic Translation, a theory that combines Peirce’s interpretive semiotics and Wittgenstein’s notions of rule-following and complex-fact. I seek to show that this approach is particularly adroit at the task of making the sometimes cryptic philosophy of Ludwig Wittgenstein accessible to readers. To support this assertion, I compare and analyze several canonical translations of the Tractatus with possible semiosic translations. The results show that Wittgenstein’s work (...) throughout its different phases displays a continuity that reaches a genuine abductive peak in the Philosophical Investigations. This abductive, usage-based turn is, nonetheless, announced in the Tractatus in terms of a quest for semiotic accuracy. (shrink)

This paper proposes a conceptual framework of multiversional narrative processing, or multiversionality. Multiversionality is the consideration of multiple possible event sequences for an incomplete narrative during reception, from reading a novel to listening to the story of a friend’s day. It occurs naturally and is experienced in a wide range of cases, such as suspense, surprise, counterfactuals, and detective stories. Receiving a narrative, we propose, is characterized by the spontaneous creation of competing interpretive models of the narrative that are then (...) used to create predictions and projections for the narrative’s future. These predictions serve as a mechanism for integrating incoming information and updating the narrative model through prediction error, without completely eliminating past versions. We define this process as having three aspects: (1) constrained expectations, (2) preference projection, and (3) causal extrapolation. Constrained expectations and preference projections respectively create the bounds and subjective desires for a narrative’s progress, while causal extrapolation builds, reworks, and maintains the potential models for understanding the narrative. We offer multiversionality as a novel framework for thinking about narrative, social cognition, and decision making that presents adaptive benefits and future directions for empirical study. (shrink)

When people retell stories, what guides their retelling? Most previous research on story retelling and story comprehension has focused on information accuracy as the key measure of stability in transmission. This paper suggests that there is a second, affective, dimension that provides stability for retellings, namely the audience affect of surprise. In a large-sample study with multiple iterations of retellings, we found evidence that people are quite accurate in preserving all degrees of surprisingness in serial reproduction – even when the (...) event that produced the surprisingness in the original story is dropped or changed. Thus, we propose that the preservation of affect is an implicit goal of retelling: not merely do retellers recall highly surprising events better, but rather they register all levels of surprisingness precisely and aim to surprise their implied audience to same degree. This study used 2,389 participants. (shrink)

Readers assume that commonplace properties of the real world also hold in realistic fiction. They believe, for example, that the usual physical laws continue to apply. But controversy exists in theories of fiction about whether real individuals exist in the story’s world. Does Queen Victoria exist in the world of Jane Eyre, even though Victoria is not mentioned in it? The experiments we report here find that when participants are prompted to consider the world of a fictional individual (“Consider the (...) world of Jane Eyre…”), they are willing to say that a real individual (e.g., Queen Victoria) can exist in the same world. But when participants are prompted to consider the world of a real individual, they are less willing to say that a fictional individual can exist in that world. The asymmetry occurs when we ask participants both if a real person is in the character’s world and if the person would appear there. However, the effect is subject to spatial and temporal constraints. When the person and the character share spatial and temporal settings, interchange is more likely to occur. These results shed light on the author’s implicit contract with the reader, which can license the reader to augment a fictional world with features that the author only implicates as part of the work’s background. (shrink)

When we read narrative texts such as novels and newspaper articles, we segment information presented in such texts into discrete events, with distinct boundaries between those events. But do our eyes reflect this event structure while reading? This study examines whether eye movements during the reading of discourse reveal how readers respond online to event structure. Participants read narrative passages as we monitored their eye movements. Several measures revealed that event structure predicted eye movements. In two experiments, we found that (...) both early and overall reading times were longer for event boundaries. We also found that regressive saccades were more likely to land on event boundaries, but that readers were less likely to regress out of an event boundary. Experiment 2 also demonstrated that tracking event structure carries a working memory load. Eye movements provide a rich set of online data to test the cognitive reality of event segmentation during reading. (shrink)