Learning to Reach to Locations Encoded from Imaging Displays

We examined the use of hand gestures while people solved spatial reasoning problem in which they had to infer motion from static diagrams (mental animation problems). In Experiment 1, participants were asked to think aloud while solving mental animation problems. They gestured on more than 90% of problems, and most gestures expressed information about the component motions that was not stated in words. Two further experiments examined whether the gestures functioned in the mechanical inference process, or whether they merely served functions of expressing or communicating the results of this process. In these experiments, we examined the effects of instructions to think aloud, restricting participants' hand motions, and secondary tasks on mental animation performance. Although participants who were instructed to think aloud gestured more than control groups, some gestures occurred even in control conditions. A concurrent spatial tapping task impaired performance on mechanical reasoning, whereas a simple tapping task and restricting hand motions did not. These results indicate that gestures are a natural way of expressing the results of mental animation processes and suggest that spatial working memory and premotor representations are involved in mental animation. They provide no direct evidence that gestures are functional in the thought process itself, but do not rule out a role for overt gestures in this type of spatial thinking.     

The cognitive adequacy of Allen's interval calculus for qualitative spatial representation and reasoning

Qualitative spatial reasoning (QSR) is often claimed to be cognitively more plausible than conventional numerical approaches to spatial reasoning, because it copes with the indeterminacy of spatial data and allows inferences based on incomplete spatial knowledge. The paper reports experimental results concerning the cognitive adequacy of an important approach used in QSR, namely the spatial interpretation of the interval calculus introduced by Allen (1983). Knauff, Rauh and Schlieder (1995) distinguished between the conceptual and inferential cognitive adequacy of Allen's interval calculus. The former refers to the thirteen base relations as a representational system and the latter to the compositions of these relations as a tool for reasoning. The results of two memory experiments on conceptual adequacy show that people use ordinal information similar to the interval relations when representing and remembering spatial arrangements. Furthermore, symmetry transformations on the interval relations were found to be responsible for most of the errors, whereas conceptualneighborhood theory did not appear to correspond to cognitively relevant concepts. Inferential adequacy was investigated by two reasoning experiments and the results show that in inference tasks where the number of possible interval relations for the composition is more than one, subjects ignore numerous possibilities and interindividually prefer the same relations. Reorientations and transpositions operating on the relations seem to be important for reasoning performance as well, whereas conceptual neighborhood did not appear to affect the difficulty of reasoning tasks based on the interval relations.     

Qualitative Spatial Reasoning for Topological Map Learning

Abstract

In this paper we investigate the application of qualitative spatial reasoning methods for learning the topological map of an unknown environment. We develop a topological mapping framework that achieves robustness against ambiguity in the available information by tracking all possible graph hypotheses simultaneously. We then exploit spatial reasoning to reduce the space of possible hypotheses. The considered constraints are qualitative direction information and the assumption that the map is planar. We investigate the effects of absolute and relative direction information using two different spatial calculi and combine the approach with a real mapping system based on Voronoi graphs.     

Expert Algorithmic and Imagistic Problem Solving Strategies in Advanced Chemistry

Abstract

Visualization and imagistic reasoning appear central to expert practice in science; however, expert use of these strategies on authentic tasks has not been examined in detail. This study documents how science experts use both algorithms and imagistic reasoning to solve problems. Using protocol analysis, we report expert chemists' preferential use of algorithms for solving spatial problems and imagistic reasoning for deducing spatial transformations. We observed experts employ algorithms to solve the majority of spatial tasks while reserving imagistic strategies to solve a class of tasks that required translating between representations. Strategy used varied widely among experts and tasks.     

Modelling Dynamic Spatial Systems in the Situation Calculus

Abstract

We propose and systematically formalise a dynamical spatial systems approach for the modelling of changing spatial environments. The formalisation adheres to the semantics of the situation calculus and includes a systematic account of key aspects that are necessary to realize a domain-independent qualitative spatial theory that may be utilised across diverse application domains. The spatial theory is primarily derivable from the all-pervasive generic notion of “qualitative spatial calculi” that are representative of differing aspects of space. In addition, the theory also includes aspects, both ontological and phenomenal in nature, that are considered inherent in dynamic spatial systems. Foundational to the formalisation is a causal theory that adheres to the representational and computational semantics of the situation calculus. This foundational theory provides the necessary (general) mechanism required to represent and reason about changing spatial environments and also includes an account of the key fundamental epistemological issues concerning the frame and the ramification problems that arise whilst modelling change within such domains. The main advantage of the proposed approach is that based on the structure and semantics of the proposed framework, fundamental reasoning tasks such as projection and explanation directly follow. Within the specialised spatial reasoning domain, these translate to spatial planning/re-configuration, causal explanation and spatial simulation. Our approach is based on the hypothesis that alternate formalisations of existing qualitative spatial calculi using high-level tools such as the situation calculus are essential for their utilisation in diverse application domains such as intelligent systems, cognitive robotics and event-based GIS.     

Qualitative Spatial Reasoning in Interpreting Text and Narrative

Abstract

Simple natural language texts and narratives often raise problems in commonsense spatial knowledge and reasoning of surprising logical complexity and geometric richness. In this article, I consider a dozen short texts—five taken from literature, the remainder contrived as illustrations—and discuss the spatial reasoning involved in understanding them. I conclude by summarizing their common features, and by tentatively drawing some morals for research in this area.     

Localization,Exploration, and Navigation Based on Qualitative Angle Information

Abstract

Three of the major problems in building autonomous mobile robots are localization, exploration, and navigation. This paper investigates how well different qualitative methods based on angle information, most of them originally invented for representation of spatial knowledge, are suited for addressing these problems. It combines results from discrete and computational geometry with methods from qualitative spatial reasoning, gaining some new insights on the complexity of robot navigation. It turns out that essentially only with panoramas (special roundviews) the qualitative localization problem can be solved in a satisfactory manner. The exploration problem (qualitative map building), remains difficult for all considered approaches.     

The Space within Fisherman's Folly: Playing with a Puzzle in Mereotopology

Abstract

In this paper we propose a spatial ontology for reasoning about holes, rigid objects and a string, taking a classical puzzle as a motivating example. In this ontology the domain is composed of spatial regions whereby a theory about holes is defined over a mereotopological basis. Within this theory we define a data structure, named chain, that facilitates a clear and efficient representation of the puzzle states and its solution.     

Revisiting Perspective-Taking: Can People Maintain Imagined Perspectives?

Abstract

Three experiments were conducted to examine whether people can adopt and maintain imagined perspectives in the absence of target information. The task used entailed providing information about an imagined perspective in advance of target information to examine whether this would facilitate perspective-taking performance and reduce or eliminate alignment effects that are commonly reported in the literature. The three experiments employed different types of spatial environments: an environment learned from navigating a computer screen (Experiment 1), and an immersive environment that was either remote (Experiment 2) or immediate (Experiment 3) at the time of retrieval. Across the three experiments, results showed that information about an imagined perspective can be utilized ahead of target information. Furthermore, they suggested that alignment effects can be reduced as a result of processing information about perspective ahead of target information, but only when reasoning about specific nonimmediate spatial relations (Experiments 1 and 2). Results are discussed in connection with previous findings on spatial updating and the organizational structure of spatial memory.     

Environmental reference systems for large-scale spaces

Human navigation in well-known environments is guided by stored memory representations of spatial information. In three experiments (N = 43) we investigated the role of different spatial reference systems when accessing information about familiar objects at different locations in the city in which the participants lived. Our results indicate that two independent reference systems underly the retrieval of spatial knowledge. Environmental characteristics, e.g., the streets at an intersection, determine which headings are easier to imagine at a given location and lead to differences in accessibility of spatial information (orientation-specific behavior). In addition, access to spatial information depends on the relative direction of a location with respect to the imagined heading, such that information about locations imagined in front of oneself is easier to access than about locations towards the back. This influence of an egocentric reference system was found for environmental knowledge as well as map-based knowledge. In light of these reference system effects, position-dependent models of spatial memory for large-scale environments are discussed. To account for the simultaneous effect of an environmental and an egocentric reference system, we present a 2-level model of spatial memory access.     

Spatial Thinking in Undergraduate Science Education

Spatial thinking is central to many scientific domains and professions spatial ability predicts success and participation in science. However spatial thinking is not is not emphasized in our educational system. This paper presents a selective review of four types of studies regarding spatial thinking in undergraduate science curricula; (1) correlational studies examining the relations between measures of spatial ability and performance in science disciplines, (2) studies that attempt to train aspects of spatial thinking, (3) studies of how students understand specific spatial representations in sciences (4) studies that use dynamic spatial representations to promote scientific understanding. For each type of study, the evidence is critically evaluated and conclusions are drawn about how to nurture spatial thinking in science.     

On Embedding a Qualitative Representation in a Two-Dimensional Plane

Abstract

This paper discusses embedding in a two-dimensional plane a symbolic representation for spatial data using the simple objects, points (P), lines (L), circuits (C), and areas (A). We have proposed PLCA as a new framework for a qualitative spatial reasoning. In a PLCA expression, the entire figure is represented in a form in which all the objects are related. We investigate the conditions for two-dimensional realizability of a PLCA expression, and derive the relation that the numbers of objects in a PLCA expression should have. In this process, we use the well-known Euler's formula. We also give an algorithm for drawing the figure of the PLCA expression that satisfies this condition in a two-dimensional plane and prove its correctness. The algorithm generates a quantitative expression from qualitative expression.     

Approximate qualitative spatial reasoning

Qualitative relations between spatial regions play an importantrole in the representation and manipulation of spatial knowledge.The RCC5 and RCC8 systems of relations,used in the Region-Connection Calculus, are of fundamentalimportance. These two systems deal with ideal regions havingprecisely determined location. However,in many practical examples of spatial reasoning,regions are represented by finite approximations rather than known precisely.Approximations may be given by describing how a regionrelates to cells forming a partition of the space underconsideration. Although the RCC5 and RCC8 systems have beengeneralized to ``egg-yolk' regions, in order to modelcertain types of vagueness, their extension to regionsapproximated in this way has not been discussed before.This paper presents two methods, the syntactic and the semantic, by which the RCC5 and RCC8 systemsmay be defined for approximate regions. The syntactic uses algebraicoperations on approximate regions which generalize operations on preciseregions. The semantic method makes use of the set of preciseregions which could be the intended interpretation of anapproximate region. Relationships between these two methods arediscussed in detail.alternative to navigation training with a map.     

Space,Language and Ontology: A Response to Davis

Abstract

Ernest Davis' article “Qualititative Spatial Reasoning in Interpreting Text and Narrative” discusses challenges that the interpretation of natural language appears to raise for the formalization of commonsense spatial reasoning. Davis finds these to be of “surprising logical complexity,” but also “erratic” in that they do not show a logical structuring of the problem space that could guide productive research. In this response I argue that much of the apparent lack of structure Davis laments is due to the very style of formal modeling he pursues. By augmenting logical considerations with substantial input from other disciplines and by adopting a heterogeneous and modular approach to formalization, I suggest that the problem space is by no means as ill-structured as Davis presents it.     

On early cognitive mapping

In this paper we examine the nature of theearly cognitive map – the beginnings of acognitive map formed from one's earlyimpressions of the environment one is in. Twodistinct paradigms have emerged from ourstudies of what information is initially identified in a cognitive map. The first, which weterm a space-based approach, emphasises makingexplicit the spatial extent of the currentlocal environment. The second emphasises makingexplicit the relationships between objects inthe local environment and we call this anobject-based approach. For both paradigms weexamine the psychological literature to findsupport for the approach and the roboticists'attempts at implementing the idea. We arguethat a space-based approach is the moreappropriate way to compute an early cognitivemap. In particular, we find that Siegel andWhite's (1975) object-based hypothesis, whichstates that the developmental progression of acognitive map is from landmark to route tosurvey map, is not supported. The space-basedparadigm underpins our own work in this areaand we outline our own space-based theory forcomputing an early cognitive map.     

Modeling visuospatial reasoning

I apply my proposed modification of Soar/Spatial/Visual System and Kosslyn’s (1983) computational operations on images to problems within a 2 × 2 taxonomy that classifies research according to whether the coding involves static or dynamic relations within an object or between objects (Newcombe & Shipley, 2015). I then repeat this analysis for problems that are included in mathematics and science curricula. Because many of these problems involve reasoning from diagrams Hegarty’s (2011) framework for reasoning from visual-spatial displays provides additional support for organizing this topic. Two more relevant frameworks specify reasoning at different levels of abstraction (Reed, 2016) and with different combinations of actions and objects (Reed, 2018). The article concludes with suggestions for future directions.     

Reasoning about Depth and Motion from an Observer's Viewpoint

ABSTRACT

The goal of this paper is to present a logic-based formalism for representing knowledge about objects in space and their movements, and show how this knowledge could be built up from the viewpoint of an observer immersed in a dynamic world. In this paper space is represented using functions that extract attributes of depth, size and distance from snapshots of the world. These attributes compose a novel spatial reasoning system named Depth Profile Calculus (DPC). Transitions between qualitative relations involving these attributes are represented by an extension of this calculus called Dynamic Depth Profile Calculus (DDPC). We argue that knowledge about objects in the world could be built up via a process of abduction on DDPC relations.     

The mitigation, management, and survivability of asteroid/comet impact with Earth

The chances that Earth will collide with a significant near earth object (NEO) within the next century are very small, but such a collision is possible, would be catastrophic, and could happen at any time. Much discussion has been devoted to methods of diverting these objects away from Earth through the use of space technology. However, if these efforts are unsuccessful, we would need to implement effective strategies to survive the event, no matter how cataclysmic. To date, disaster management for various impact scenarios has not been addressed (except in novels and Hollywood films). An impact disaster may be many orders of magnitude greater than any disaster the human species has ever experienced. Initially, technology and experience gained in other large-scale disasters will most likely form the foundation of how these impact events will be managed and classified. Given the size and energy of the projectile, the estimated area of damage, and whether impact effects might be localized or global in nature, we can begin to build basic disaster response scenarios, anticipate public health concerns, and formulate questions in need of answers. Questions we must deal with include: what will be required technologically, sociologically, and medically to survive? What types of evacuation plans and warning systems might be required? Capabilities in need of further investigation include: technological protection strategies related to ‘impact winter’, expanded chemical hazard control methodologies, food storage and production, roles of national governments, and international cooperation. Whatever the magnitude and severity of the event, we must reflect on what we know, what capabilities we can apply, develop or adapt, and seriously investigate what might be done to manage it and survive.