Qualitative Spatial Reasoning

Everyone who endorses the categorial distinction between objects and events must confront a general question: how do these two types of entities relate to one another? Here we are especially interested in what is typically regarded as the basic relational tie between the two, namely, that objects may be said to participate or take part in events, whereas events befall or happen to their participants. The exact nature of this participation relation is philosophically contentious and may depend on how the two categories of objects and events are construed in the first place. Regardless of its metaphysical characterization, however, a number of questions arise concerning its formal features and the general laws that govern its behavior. In particular, since both objects and events can be mereologically structured, we are interested in the formal laws that govern the interaction between participation and parthood. If objects are events, as some perdurantists maintain, then participation just is parthood. But what if objects and events form genuinely distinct categories? What, then, is the relationship between being part of something and taking part in something?

In this paper, we present a framework abstracting motion by creating a qualitative representation of classes describing motion, and use the continuity constraints implicitly embedded in the semantics of these classes to create a framework that enables plausible reasoning about them. In particular, we propose a topology-based calculus of motion whose primitive is a motion class. We subsequently construct a set of primitive motion classes that exhaustively describes the change in topology between two moving objects, and show how compound motion classes are formed from these primitive motion classes using continuity constraints we make explicit. We use composition tables to define queries in the spatio-temporal domain and enable the extension of the classes to reason about the change in topology among three objects as they move.

The world is now more urban than rural for the first time in the history of our species, yet there are no answers to many basic questions about the influences of urban morphology on the way we live. With more than three billion people to house in an environment of growing urban density, developer driven construction and failing public infrastructure, life is often being degraded despite fast paced technological advances promising improvement.

As could be expected in a post-industrial age, urban development is now an assembly of specialised functions, often unconnected and without the capacity to adequately measure its impact on the people affected.  An ‘Urban Mereology’, over the long term, may help redefine the roles of transport engineering, architecture and town planning. This is not though an idealised hunt for the Urpflanze of urban form. It is a straight forward categorisation of well recognised, often spoken of, relationships manifest in the current knowledge. 

The framework or perspective used to investigate a system produces an analysis with that perspective. If a city is viewed as a sequence of activities, a segmented procession, then as Alexander said, you get a tree but he famously argued that a city is not a tree. Urban design informed by vehicle movement evolves a traffic network. A mereological approach is built on relationships and combines a number of land uses. It represents the world as it is. 

A mereological perspective is also a recognition that streets, buildings and public spaces have multiple functions and their combinations produce complex relationships. Buildings and public spaces have human impacts as significant as roads and streets. (This is a separate notion from, and does not undermine, the street as a “fundamental building-block of urban structure”).

In this paper we give an axiom system of a non-linear 4-valued logic which we call a de Morgan logic (ML), whose Lindenbaum algebra is the de Morgan algebra with implication (MI-algebra), and show that (1) For every MI-algebra L, there is a quotient MI-algebra L such that it is embeddable to the simplest 4-valued MI-algebra M = {0, a, b, 1}; (2) The Lindenbaum algebra of ML is the MI-algebra; (3) The completeness theorem of ML is established; (4) ML is decidable.

Spatial problems and a variety of abstract problems can be solved by humans with more ease if the problem can be visualized and/or manipulated. Elaborating on the differences and interplay between representing spatial problems and solving them, this paper focuses on exploring the qualities of a strings and pins problem solving domain. This domain is compared to the straightedge and compass domain of Euclidean geometry. The strings and pins domain is described and two case studies are analyzed: (i) a strings and pins solution of the shortest path problem and (ii) a strings and pins solution to the Voronoi diagram problem; both approaches are compared to a formal solution. Differences and similarities between the straightedge and compass domain and the strings and pins domain are analyzed, and features and limitations of constructive and depictive geometry are discussed. Different problem solving phases are distinguished. Furthermore, cognitive aspects of different problem solving app...

This paper presents the results of a quasi-experimental research study conducted with pre-service primary education teachers in Croatia aged 19 to 23. The purpose of the research was to evaluate an alternative approach to learning and teaching geometry to develop visualization skills and geometric thinking and achieve better learning outcomes. The alternative teaching approach was based on van Hiele's theoretical framework, on the visual-analytical method of directed observation, and on the balancing of visual, linguistic, and symbolic expressions. The control group was taught in the traditional way. In order to collect data on the research participants, the three tests were used before and after teaching: the first to measure the level of geometric thinking, the second to gain insight into geometric knowledge and visual skills, and the third to measure special visual-spatial ability. At the beginning of teaching, there were no statistically significant differences among the research participants. After teaching, the progress of the participants in the experimental group was statistically significant compared to the participants of the control group.

Traditional computational models of geographic phenomena offer no room for imperfection. Underlying this tradition is the simplifying assumption that reality is certain, crisp, unambiguous, independent of context, and capable of quantitative representation. This paper reports on initial work which explicitly recognises that most geographic information is intrinsically imperfect. Based on an ontology of imperfection the paper explores a formal model of imperfect geographic information using multi-valued logic. The development of Java software able to assist with a geodemographic retail site assessment application is used to illustrate the utility of a formal approach. While there may be consensus on the complex multi-dimensional nature of imperfection in geographic information, there is at best limited consensus in the literature on what these different dimensions actually are. Terms such as error, uncertainty, accuracy, precision, detail are subject to a range of different definitions and interpretations across the different disciplines that comprise GIS . The starting point for this paper, then, is to introduce a simple ontology of the key aspects of imperfection. It is not the intention to suggest that the ontology and definitions developed below are necessarily exclusive of other ontologies of imperfection. However, it is argued in section 3 that the ontology introduced here is congruent with formal interpretations of imperfection. Computer, Environment and Urban Systems v25 pp. 89-103. Knowledge about reality is gained through observations. Observations are therefore first class objects in our account, rather than the underlying objects that are observed (Worboys, 1998a). Observations are imperfect in the sense that they can never fully or correctly reflect all aspects of reality. Imperfection is therefore the root of our ontology, as the concept refers generally to the inevitable deviations from perfection when observing reality. Imperfection can be thought of as comprising two distinct orthogonal concepts: error and imprecision. Error, or inaccuracy, concerns a lack of correlation of an observation with reality; imprecision concerns a lack of specificity in representation. Observations will usually be inaccurate and imprecise, but error and imprecision are orthogonal concepts since the level of accuracy of an observation is not implied by the level of precision, nor vice versa. Intuitively, the statement "York is in England" is at the same time more accurate and less precise than the statement "York is in Lancashire". The general definitions of accuracy and precision above correspond closely to the more specialised statistical definitions of the terms in common usage (see . Any observation of reality will be subject to imprecision: Veregin (1999) discusses some of the different causes and types of imprecision. Granularity is closely related, but not identical to imprecision. Granularity refers to the existence of clumps or grains in information, in the sense that individual elements in the grain cannot be distinguished or discerned apart. Granulation is therefore the result of distinct entities becoming indiscernible due to the imprecision in an observation. Observations or representations of coarser granularity offer less detail, for example where the clumping of information into pixels in remotely sensed images may prevent sub-pixel entities being distinguished . Vagueness, however, is a special type of imprecision which concerns the existence of indeterminate borderline cases. "Yorkshire is in England" is not a vague statement (both Yorkshire and England have clearly defined national or international boundaries), but is an imprecise statement. Although intuitively more precise, "Yorkshire is in the East of England" is a vague statement, since the concept of the East of England has borderline cases. Vagueness and imprecision are not equivalent, but every vague statement must also be imprecise, because of the lack of specificity at the boundary.

FLUX belongs to the high-level programming lan­ guages for cognitive agents that have been devel­ oped in recent years. Based on the established, general action representation formalism of the Flu­ ent Calculus, FLUX allows to implement complex strategies in a concise and modular fashion. In this paper, we extend the FLUX language to reason about domains involving continuous change and where actions occur concurrently. Using constraint logic programming, we show that this reasoning is performed in an efficient way.

This study has two main objectives. The first is to specify the nature of the mental representation and processes underlying spatial reasoning with diagrams and sentences. The second is to investigate whether mental representations reproduce geometrical relations relative to spatial reference frames. Forty participants solved 64 spatial reasoning problems that were displayed using diagrams or sentences. Problems varied with respect to their logical structure and geometrical content. We measured the premise's inspection times, the responses, and the response times. Problems were significantly (p < .01) easier to represent and solve when displayed as diagrams than as sentences, indicating that participants constructed mental models. Mental representations and spatial deductions also varied consistently with the geometrical content, suggesting that mental models reproduced this content relative to a viewer‐centred reference frame.

We propose a framework for robot programming which allows the seamless integration of explicit agent programming with decision-theoretic planning. Specifically, the DTGolog model allows one to partially specify a control program in a highlevel, logical language, and provides an interpreter that, given a logical axiomatization of a domain, will determine the optimal completion of that program (viewed as a Markov decision process). We demonstrate the utility of this model with results obtained in an office delivery robotics domain.

In this paper, we present some preliminary results about the connections existing between qualitative and discrete constraint networks. We present a natural encoding of any qualitative network N into a discrete one P such that the constraints of N become the variables of P and the constraints of P are defined by the weak composition table of the used qualitative algebra. We then introduce some properties about the (global) consistency of networks, circumscribing conditions under which the two models are equivalent. We also relate some domain filtering consistencies (such as generalized arc consistency) of discrete networks encoding qualitative ones with •-consistency, where • denotes the weak composition of the qualitative calculus.

TELEIOS is a recent European project that addresses the need for scalable access to petabytes of Earth Observation data and the discovery of knowledge that is hidden in them. TELEIOS builds on scientific database technologies (array databases, SciQL, data vaults) and Semantic Web technologies (stRDF and stSPARQL) implemented on top of a state of the art column store database system (MonetDB). In this paper we outline the gains that Earth Observation organizations can have from these technologies by presenting a detailed example of a fire monitoring service that we have completed.

Geo-ontologies have a key role to play in the development of the geospatial-semantic web, with regard to facilitating the search for geographical information and resources. They normally hold large amounts of geographic information and undergo a continuous process of revision and update. Hence, means of ensuring their integrity are crucial and needed to allow them to serve their purpose. This paper proposes the use of qualitative spatial reasoning as a tool to support the development of a geo-ontology management system. A new framework for the representation of and reasoning over geo-ontologies is presented using the web ontology language (OWL) and its associated reasoning tools. Spatial reasoning and integrity rules are represented using a spatial rule engine extension to the reasoning tools associated with OWL. The components of the framework are described and the implementation of the spatial reasoning engine is presented. This work is a step towards the realisation of a complete geo-ontology management system for the semantic web.

The problem of temporally situating events in language has been approached by a number of philosophical techniques, including Davidson's particularist theory of event individuation [6, 5] and Kim's property exemplification theory [16]. Both of these theories have been developed within linguistic semantic traditions, as well (cf. [24, 2] and others). However, the problem of event localization (spatially situating events) has not been discussed as extensively in the semantics literature. In this paper, I discuss the procedures for identifying where events, as expressed in natural language, are located in space. Aspects of the semantics of event localization have been recently proposed, including the notion of the "shape" of a movement [8, 39], as well as treating movement verbs as "path creation" predicates [29]. In this paper, I build on these and some additional observations to outline a more general semantics of event localization. I then outline a procedure that extends the path metaphor used for motion predicates, distinguishing between the event locus and the spatial aspect of an event. In the process, I discuss how localization is supervenient upon the participants in the events.

If Geographic Information Systems (GISs) contain multiple representations of the same geographic objects at different levels of detail, it becomes necessary to compare the different representations and assess whether they contradict each other or not. Topological information is generally considered first-class geographic information and as such the preservation of topological relations among objects in different representations manifests a critical criterion for the comparison of multiple representations and their consistency evaluation. This paper describes a framework within which the topological consistency of multiple representations can be assessed. The rational for assessing topological similarity is the monotonicity assumption of a generalization, under which the topology of any object and any topological relation between objects must stay the same through consecutive representation levels; or continuously decrease in complexity and detail. Such changes are assessed through object similarity and relation similarity, respectively. Within this framework, only those topological invariants can be changed that are at least on an ordinal scale. 1 .

In this big data modern age, enormous size of data is a challenge for the computer algorithms as well as hardware because important information is hidden in the data. Principal Component Analysis (PCA) is used to transform the data so that meaningful information becomes explicit. The huge dimensional data can be approximated with a few dimensions. Qualitative Spatial Reasoning (QSR), spatial or network, uses pairwise intersection to determine relations between objects. The 9-Intersection model is commonly used to classify the relations. The performance of QSR can be improved by reducing the number of intersections. PCA has been successfully applied to several domains including image processing, data mining and web document analysis, but its connection to QSR is nonexistent. Herein we show how (1) PCA can be applied to intersection dimension reduction for QSR spatial data, and (2) the 9-Intersection can be reduced to 4-Intersection for all spatial as well as non-spatial objects.

Spatial reasoning is a crucial component of both biological and artificial intelligence. In this work, we present a comprehensive study of the capability of current state-of-the-art large language models (LLMs) on spatial reasoning. To support our study, we created and contribute a novel Spatial Reasoning Characterization (SpaRC) framework and Spatial Reasoning Paths (SpaRP) 1 datasets, to enable an in-depth understanding of the spatial relations and compositions as well as the usefulness of spatial reasoning chains. We found that all the stateof-the-art LLMs do not perform well on the datasets-their performances are consistently low across different setups. The spatial reasoning capability improves substantially as model sizes scale up. Finetuning both large language models (e.g., Llama-2-70B) and smaller ones (e.g., Llama-2-13B) can significantly improve their F1-scores by 7-32 absolute points. We also found that the top proprietary LLMs still significantly outperform their open-source counterparts in topological spatial understanding and reasoning.

It is shown that Tarski’s set of ten axioms for the calculus of relations is independent in the sense that no axiom can be derived from the remaining axioms. It is also shown that by modifying one of Tarski’s axioms slightly, and in fact by replacing the right-hand distributive law for relative multiplication with its left-hand version, we arrive at an equivalent set of axioms which is redundant in the sense that one of the axioms, namely the second involution law, is derivable from the other axioms. The set of remaining axioms is independent. Finally, it is shown that if both the left-hand and right-hand distributive laws for relative multiplication are included in the set of axioms, then two of Tarski’s other axioms become redundant, namely the second involution law and the distributive law for converse. The set of remaining axioms is independent and equivalent to Tarski’s axiom system

Qualitative spatial reasoning (QSR) is useful for deriving logical inferences when quantitative spatial information is not available. QSR theories have applications in areas such as geographic information systems, spatial databases, robotics, and cognitive sciences. The existing QSR theories have been applied primarily to 2D. The ability to perform QSR over a collection of 3D objects is desirable in many problem domains. Here we present the evolution (VRCC-3Dþ) of RCC-based QSR from 2D to both 3D (including occlusion support) and 4D (a temporal component). It is time consuming to construct large composition tables manually. We give a divideand-conquer algorithm to construct a comprehensive composition table from smaller constituent tables (which can be easily handcrafted). In addition to the logical consistency entailment checking that is required for such a system, clearly there is a need for a spatio-temporal component to account for spatial movements and path consistency (i.e. to consider only smooth transitions in spatial movements over time). Visually, these smooth movement phenomena are represented as a conceptual neighborhood graph. We believe that the methods presented herein to detect consistency, re¯ne uncertainty, and enhance reasoning about 3D objects will provide useful guidelines for other studies in automated spatial reasoning.

Qualitative spatial reasoning (QSR) is a powerful tool in automated computer reasoning, a necessary step forward in fields like computer vision and media analysis. Stereo graphical media has rapidly become a prevalent part of technological culture, and the amount of these kinds of data that exists is staggering. Humans interpret depth information using prior knowledge that a computer lacks. This prior knowledge stems from remembered observance of the basic laws of physics. While the computer lacks the intuitive understanding of these principal physical properties, it is capable of determining more precise information through calculation. Herein the authors explore the information that can be gained from an amalgamation of QSR methods and physics, and present some preliminary results from an implementation based on this powerful combination.

The intersection between objects relates to a class of problems where either precise intersection is required or imprecise intersection is acceptable. The calculation of intersection between two 2D/3D objects is a computation-intensive process. For qualitative spatio-temporal reasoning, it is sufficient to know the existence of intersection instead of the precise intersection. In order to identify RCC8 relations, the 9-Intersection model considers the pairwise intersection of interiors, boundaries, and exteriors of objects. It was determined that the 9-Intersection is sufficient for identifying spatial relations. Later, it was shown that a 4-Intersection model is sufficient to achieve the same results making the definition (and implementation) of the RCC8 relations worth studying in greater detail. Herein we prove that the 9-Intersection model can be further reduced to almost three intersection predicates, producing a 3 +-Intersection model. This results in improved algorithmic and computational efficiency as a consequence of fewer predicates and faster intersection operations.

3D models are used in many problem domains. Typically the spatial relations between objects are approximated as necessary for human recognition of an image. For some applications, this may be insufficient; a more precise analysis may be required, and a temporal sequence of configurations of the objects may need to be considered. VRCC-3D+ is the implementation of a Region Connection Calculus (RCC) that qualitatively determines the spatial relations between 3D objects, both in terms of connectivity and obscuration. Herein we discuss how this system can be used to validate hypotheses of spatial transformation over time, and generate possible intermediate configurations. Such analyses have been performed manually in research fields such as organism evolution and development. Automation of this process has the potential to improve both the efficiency and precision of such investigations.

Computational geometry is a field that is relevant to computer graphics rendering, computational physical simulation, and countless other problem domains involving the use of image data. Efficiently determining the intersection of the boundaries, interiors, and exteriors of two 3D objects can mean the difference between a realistic and relevant simulation, and a slow program that produces results to that do not keep pace with user interaction with the object. However, the speed of these calculations is not the only area of concern. Taking into consideration the finite unit of resolution in a computer display (the pixel), the minimum change in distance the human eye can perceive, and error in the floating-point representation of numbers, it may be the case that the perceived correctness of these computations does not necessarily correspond to the accuracy with which the calculations are carried out. In this paper, we examine two of the most well-known methods of determining such intersections, as well as various programming language libraries available to perform these calculations. These existing approaches are considered with respect to limitations in human perception, display resolution, and floating point error. We also propose a new method which lends itself to exploiting the inherently parallel nature of these calculations.

Geo-ontologies have a key role to play in the development of the geospatial-semantic web, with regard to facilitating the search for geographical information and resources. They normally hold large amounts of geographic information and undergo a continuous process of revision and update. Hence, means of ensuring their integrity are crucial and needed to allow them to serve their purpose. This paper proposes the use of qualitative spatial reasoning as a tool to support the development of a geo-ontology management system. A new framework for the representation of and reasoning over geo-ontologies is presented using the web ontology language (OWL) and its associated reasoning tools. Spatial reasoning and integrity rules are represented using a spatial rule engine extension to the reasoning tools associated with OWL. The components of the framework are described and the implementation of the spatial reasoning engine is presented. This work is a step towards the realisation of a complete geo-ontology management system for the semantic web.

Qualitative spatial reasoning is important for many spatial information systems, including GISs. It is based on the manipulation of qualitative spatial relationships and is used to infer spatial relationships which are not stored explicitly in the Geographic DataBase (GDB), to answer spatial queries given partial spatial knowledge and to maintain the consistency of the GDB. This paper compares the basic approaches developed for expressing qualitative topological, orientation and direction relationships. An extension of one of the classi ed approaches is then used for the representation of directional relationships (north, south, east, etc.) between objects of arbitrary shapes and for the representation of ow direction relationships (topological relationships between objects carrying ow, e.g. road segments, utility networks, etc.) as required within a GIS.

This articles explores the mereological foundation of truthmaker semantics. Building upon Kit Fine’s abstract theory of part in [16], we engage in an exploration of the mereological assumptions that determine the construction of truthmaker semantics. Our approach yields semantics for a diverse range of logics, including substructural logics such as the associative Lambek calculus, as well as the logics of analytic containment. Furthermore, we elucidate the philosophical implications that arise from this pioneering approach.

The development of autonomous agents that perform tasks with the same dexterity as performed by humans is one of the challenges of artificial intelligence and robotics. This motivates the research on intelligent agents, since the agent must choose the best action in a dynamic environment in order to maximise the final score. In this context, the present paper introduces a novel algorithm for Qualitative Case-Based Reasoning and Learning (QCBRL), which is a case-based reasoning system that uses qualitative spatial representations to retrieve and reuse cases by means of relations between objects in the environment. Combined with reinforcement learning, QCBRL allows the agent to learn new qualitative cases at runtime, without assuming a pre-processing step. In order to avoid cases that do not lead to the maximum performance, QCBRL executes case-base maintenance, excluding these cases and obtaining new (more suitable) ones. Experimental evaluation of QCBRL was conducted in a simulated robot-soccer environment, in a real humanoid-robot environment and on simple tasks in two distinct gridworld domains. Results show that QCBRL outperforms traditional RL methods. As a result of running QCBRL in autonomous soccer matches, the robots performed a higher average number of goals than those obtained when using pure numerical models. In the gridworlds considered, the agent was able to learn optimal and safety policies.

The development of autonomous agents that perform tasks with the same dexterity as performed by humans is one of the challenges of artificial intelligence and robotics. This motivates the research on intelligent agents, since the agent must choose the best action in a dynamic environment in order to maximise the final score. In this context, the present paper introduces a novel algorithm for Qualitative Case-Based Reasoning and Learning (QCBRL), which is a case-based reasoning system that uses qualitative spatial representations to retrieve and reuse cases by means of relations between objects in the environment. Combined with reinforcement learning, QCBRL allows the agent to learn new qualitative cases at runtime, without assuming a pre-processing step. In order to avoid cases that do not lead to the maximum performance, QCBRL executes case-base maintenance, excluding these cases and obtaining new (more suitable) ones. Experimental evaluation of QCBRL was conducted in a simulated robot-soccer environment, in a real humanoid-robot environment and on simple tasks in two distinct gridworld domains. Results show that QCBRL outperforms traditional RL methods. As a result of running QCBRL in autonomous soccer matches, the robots performed a higher average number of goals than those obtained when using pure numerical models. In the gridworlds considered, the agent was able to learn optimal and safety policies.

Spatial reasoning is essential for many AI applications. In most existing systems the representation is primarily numerical, so the information that can be handled is limited to precise quantitative data. However, for many purposes the ability to manipulate high-level qualitative spatial information in a exible way would be extremely useful. Such capabilities can be proveded by logical calculi; and indeed 1st-order theories of certain spatial relations have been given 20]. But computing inferences in 1st-order logic is generally intractable unless special (domain dependent) methods are known. 0-order modal logics provide an alternative representation which is more expressive than classical 0-order logic and yet often more amenable to automated deduction than 1st-order formalisms. These calculi are usually interpreted as propositional logics: non-logical constants are taken as denoting propositions. However, they can also be given a nominal interpretation in which the constants stand for some kind of object. I show how 0-order logics can be given a spatial interpretation: constants denote regions and logical operators correspond to operations on regions which are important for characterising spatial situations. Representing certain spatial concepts requires the introduction of modal operators, interpreted as functions generating regions related in speci c ways to those denoted by their arguments. A signi cant example is the convex-hull operator whose value is the smallest convex region containing its argument. I investigate how this this operator can be captured in a multi-modal logic.

The need for a formal language in which to express and reason about spatial concepts is of crucial importance in many areas of AI and visual systems. For the last five years, spatial reasoning research by the Qualitative Spatial Reasoning Group, University of Leeds, has centred on the development and application of such a language-the RCC spatial logic. Below, we briefly describe the work of the group in this area.

Region Based Geometry (RBG) is an axiomatic theory of qualitative configurations of spatial regions. It is based on Tarski's Geometry of Solids, in which the parthood relation and the concept of sphere are taken as primitive. Whereas in Tarski's theory the combination of mereological and geometrical axioms involves set theory, in RBG the interface is achieved by purely 1st-order axioms. This means that the elementary sublanguage of RBG is extremely expressive, supporting inferences involving both mereological and geometrical concepts. Categoricity of the RBG axioms is proved: all models are isomorphic to a standard interpretation in terms of Cartesian spaces over Ê.

We define a ternary Relation Algebra (RA) of relative position relations on twodimensional directed lines (d-lines for short). A d-line has two degrees of freedom (DFs): a rotational DF (RDF), and a translational DF (TDF). The representation of the RDF of a d-line will be handled by an RA of 2D orientations, CYC t , known in the literature. A second algebra, T A t , which will handle the TDF of a d-line, will be defined. The two algebras, T A t and CYC t , will constitute, respectively, the translational and the rotational components of the RA, PA t , of relative position relations on d-lines: the PA t atoms will consist of those pairs t, r of a T A t atom and a CYC t atom that are compatible. We present in detail the RA PA t , with its converse table, its rotation table and its composition tables. We show that a (polynomial) constraint propagation algorithm, known in the literature, is complete for a subset of PA t relations including almost all of the atomic relations. We will discuss the application scope of the RA, which includes incidence geometry, GIS (Geographic Information Systems), shape representation, localisation in (multi-)robot navigation, and the representation of motion prepositions in NLP (Natural Language Processing). We then compare the RA to existing ones, such as an algebra for reasoning about rectangles parallel to the axes of an (orthogonal) coordinate system, a "spatial Odyssey" of Allen's interval algebra, and an algebra for reasoning about 2D segments.

This paper presents an approach for reasoning about ac- tion and change which appeals to the principle of Occam's razor— roughly stating that the simplest explanations are the best ones—as the underlying theme of commonsense reasoning. We conduct a pre- liminary investigation of how appealing to simplicity allows us to ad- dress some of the challenges faced when reasoning about

This paper describes tools developed at Educational Testing Service which use statistical modeling of textual corpora to provide automated assessments of student responses. Details are given for three of these systems: Critique Writing Analysis Tools for providing feedback to students, e-rater for assigning a holistic score to student essays, and c-rater, which scores responses to content-based, short-answer test or chapter

From the mid-seventeenth century onwards, Kasimbazar emerged as the English East India Company's (EIC) primary market for silk and its textiles. The region surrounding Kasimbazar was prolific in producing silk goods destined for export. Attracted by Bengal silk's substantial profitability, EIC's directors in London envisaged an expansion to regions with existing infrastructure capable of delivering high-quality raw silk and textiles. Subsequently, Mr. Streynsham Master was dispatched to Bengal as a special envoy to strategize this expansion. The establishment of the EIC's sixth factory at Malda directly resulted from this mission. However, the nascent years of the Malda settlement were fraught with challenges, leading company officials to perceive Malda as a subordinate to Hooghly and Kasimbazar with uncertain business potential. But, within two decades, consistent profits began to reshape this perception. Up until the key shifts in 1898 and 1899-EIC acquiring zamindary rights in Calcutta, establishing Fort William as the English headquarters, and the subsequent relocation of the subah capital from Dhaka to Murshidabad in 1706-interactions with local provincial rulers were mired in extortion and bribery. Nonetheless, the handsome profit margins painted a promising outlook for the EIC's future in the region. This paper delves into the initial 25 years after the Malda factory's inception. It evaluates the hurdles faced; the resolutions reached-whether through diplomacy or through petitions to distant Dhaka-the appointment of dadani merchants, the inclusion of pykers, and most notably, the trajectory of business growth and profits during this period.

of Thesis The aim of this thesis is to introduce and elaborate a new conception of the relation between wholes and parts. Wholes, I propose, can be conceived of as 'Unities', in contrast to their currently familiar conception as 'sums'. Following a clue given in the distinction which Plato draws in the Theaetetus (203c-205e) between two conceptions of a complex entity, I argue that a similar distinction can be coherently developed in modern terms. Part I is preoccupied with general conceptual and historical background. Some theoretical constraints on any theory of wholes and parts are challenged and found to be merely apparent. In Part II the conception of wholes as sums is presented, and it is extensively argued that modern discussions of wholes generally presuppose this conception. This presupposition is shared not only by authors who subscribe to the 'classical' mereological theories of Lesniewski, and Goodman, but also by theorists of holistic sympathies ...

Mereotopologies have traditionally been defined in terms of the intersection of point sets representing the regions in question. Whilst these semantic schemes work well for purely topological aspects, they do not give any semantic insight into the degree to which the different mereotopological relations hold. This paper explores this idea of a distance based interpretation for mereotopology. By introducing a distance measure between x and y, and for various Boolean combinations of x and y, we show that all the RCC8 relations can be distinguished. We then introduce a distance measure which combines these individual measures which we show reflect different paths through the RCC8 conceptual neighbourhood-i.e. the measure decreases/increases monotonically given certain monotonic transitions (such as one region expanding). There are several possible applications of this revised semantics; in the second half of the paper we explore one of these in some depth-the problem of abstracting mereotopological relations from noisy video data, such that the sequences of qualitative relations between pairs of objects do not suffer from "jitter". We show how a Hidden Markov Model can exploit this distance based semantics to yield improved interpretation of video data at a qualitative level.

In addition, based on the demands of users of the automated scoring technology, tools have been developed that perform more detailed evaluations of student writing. One such application is Critique Writing Analysis Tools. Critique and erater are embedded in a broader writing instruction application, Criterion sm Online Essay Evaluation (see http://www.etstechnologies.com). Critique performs a number of evaluations on a student essay related to errors in grammar (Chodorow and Leacock, 2000), usage, and mechanics, comments on style, and analysis of essay-based discourse (organization and development) (Burstein et al, 2001 and Burstein and Marcu, 2003, and Burstein, Marcu and Knight, forthcoming). Many of these capabilities use machinelearning approaches to model each particular kind of analysis. To develop such tools requires large sets of human annotated data, where judges have annotated information required to train a system to evaluate a particular kind of essay characteristic. For example, to build a capability to identify sentence fragments, a corpus of essay data needs to be annotated for this kind of ungrammatical sentence. A capability exists that identifies essaybased discourse elements in essays, for example, thesis statements, and conclusions. To do this, human judges annotated a corpus of essays for these particular kinds of discourse elements.

Automated essay scoring is now an established capability used from elementary school through graduate school for purposes of instruction and assessment. Newer applications provide automated diagnostic feedback about student writing. Feedback includes errors in grammar, usage, and mechanics, comments about writing style, and evaluation of discourse structure. This paper reports on a system that evaluates a characteristic of lower quality essay writing style: repetitious word use. This capability is embedded in a commercial writing assessment application, Criterion SM. The system uses a machine-learning approach with word-based features to model repetitious word use in an essay. System performance well exceeds several baseline algorithms. Agreement between the system and a single human judge exceeds agreement between two human judges.

E-rater" is an operational automated essay scoring application that combines several natural language processing (NLP) tools for the purpose of identifying linguistic features in essay responses to assess the quality of the text. The application currently identifies a variety of syntactic, discourse, and topical analysis features. Two clear visions have guided e-rater's development. First, new linguistically based features were to be added to strengthen connections between human scoring guide criteria and e-rater scores. Secondly, e-rater was to be adapted to provide explanatory feedback about writing quality automatically. This paper provides two examples of the flexibility of e-rater's modular architecture for continued application development toward these goals. The paper discusses how additional features from rhetorical parse trees were integrated into e-rater and how the salience of automatically generated discourse-based essay summaries was evaluated for use as instructional feedback through the reuse of e-rater's topical analysis module. (Contains 10 references.) (Author/SLD) Reproductions supplied by EDRS are the best that can be made from the original document.

K-12 education standards in the U.S. require all students to read complex texts across many subject areas. The Language Muse TM Activity Palette is a web-based language-instruction application that uses NLP algorithms and lexical resources to automatically generate language activities and support English language learners' content comprehension and language skills development. The system's online platform for activity generation, scoring, and feedback is scalable for MOOCs, as well as for other online learning settings.

Developing agents for simulation environments is usually the responsibility of computer experts. However, as domain experts have superior knowledge of the intended agent behavior, it is desirable to have domain experts directly specifying behavior. In this paper we describe a system which allows non-computer experts to specify the behavior of agents for the RoboCup domain. An agent designer is presented with a Graphical User Interface with which he can specify behaviors and activation conditions for behaviors in a layered behavior-based system. To support the testing and debugging process we are also developing interfaces that show, in real-time, the world from the agents perspective and the state of its reasoning process.

For qualitative spatial reasoning, there are various dimensions of objects. A considerable amount of effort has been devoted to 2D representation and analysis of spatial relations. Here we present an exposition for 3D objects. There are three types of binary relations between pairs of objects: topological connectivity, cardinal directions, and distance relations. The combinations of these relations can provide additional useful knowledge. The spatial databases include data and the spatial relations to facilitate end-user spatial querying, it also is important to associate natural language with these relations. Some work has been done in this regard for line-region and region-region topological relations in 2D, and very recent work has initiated the association between natural language, topology, and metrics for 3D objects. However, prior efforts have lacked rigorous analysis, expressive power, and completeness of the associated metrics. Herein we present a detailed study of new metrics required to bridge the gap between topological connectivity and size information for integrating reasoning in spatial databases. The complete set of metrics that we present should be useful for a variety of applications dealing with 3D objects including regions with vague boundaries.