To Örebro University

The AAAI-13 Workshop Program, a part of the 27th AAAI Conference on Artificial Intelligence, was held Sunday and Monday, July 14-15, 2013, at the Hyatt Regency Bellevue Hotel in Bellevue, Washington, USA. The program included 12 workshops covering a wide range of topics in artificial intelligence, including Activity Context-Aware System Architectures (WS-13-05); Artificial Intelligence and Robotics Methods in Computational Biology (WS-13-06); Combining Constraint Solving with Mining and Learning (WS-13-07); Computer Poker and Imperfect Information (WS-13-08); Expanding the Boundaries of Health Informatics Using Artificial Intelligence (WS-13-09); Intelligent Robotic Systems (WS-13-10); Intelligent Techniques for Web Personalization and Recommendation (WS-13-11); Learning Rich Representations from Low-Level Sensors (WS-13-12); Plan, Activity,, and Intent Recognition (WS-13-13); Space, Time, and Ambient Intelligence (WS-13-14); Trading Agent Design and Analysis (WS-13-15); and Statistical Relational Artificial Intelligence (WS-13-16)

This paper presents the Multitask, Multilingual, Multimodal Language Generation COST Action – Multi3Generatio(CA18231), an interdisciplinary networof research groups working on different aspects of language generation. This "meta-paper" will serve as reference for citationof the Action in future publications. It presents the objectives, challenges and a the links for the achieved outcomes.

Cognitive media studies has developed as an area of research at the interface of disciplines as diverse as aesthetics, psychology, neuroscience, film theory, and cognitive science. In this context, the focus of this talk is on the foundational significance of artificial intelligence and visuo-spatial cognition and computation for the design of inte-grated analytical–empirical methods for the (multi-modal) analysis of human behaviour data vis-a-vis a range of digital visuo-auditory narrative media (e.g., narrative film). The presentation focusses on the methodological foundations and assistive technologies for systematic formalization and empirical analyses aimed at, for instance, the generation of evidence, establishing and characterizing correlates between principles for the synthesis of the moving image (e.g., from a cinematographic viewpoint), and its perceptual recipient effects and influence on observers.

In the backdrop a range of completed and ongoing experiments, we emphasize the core results on the semantic interpretation of human behaviour vis-a-vis narrative film and its visuo-auditory reception. We demonstrate the manner in which AI-based models for machine coding of narrative, and relational inference and learning serves as basis to externalize explicit and inferred knowledge about embodied visuo-auditory reception, e.g., using modalities such as diagrammatic representations, natural language, complex (dynamic) data visualizations.

Demonstration: The presentation will particularly showcase methods and tools developed to perform perceptual narrativisation or sensemaking with multi-modal, dynamic human-behaviour data (combining visuo-spatial imagery such as film/video, eye-tracking, head-tracking during a perception task) for a chosen set of experimental material based on existing films, as well as lab-developed experimental content.

We demonstrate the role of commonsense inference toward the modeling of qualitative notions of space and spatial change within a dynamic setup. The inference patterns are connected to those that are required to handle the frame problem whilst modeling inertia, and the causal minimisation of (Lin 1995) that is required to account for the ramifications of occurrences. Such patterns are both useful and necessary in order to operationalize a domain-independent qualitative spatial theory that is re-usable in arbitrary dynamic spatial systems, e.g., for spatial planning and causal explanation tasks. The illustration, grounded in the context of embedding arbitrary 'qualitative spatial calculi' within the situation calculus, utilizes topological and orientation calculi as examples.

A dynamical systems approach for modeling changing spatial environments is formalised. The formalisation adheres to the representational and computational semantics of situation calculus and includes a systematic account of all aspects necessary to implement a domain-independent qualitative spatial theory that is applicable across diverse application areas. Foundational to the formalisation is a situation calculus based causal theory and a generalised view of qualitative spatial calculi that encompass one or more spatial domains. Furthermore, aspects considered inherent to dynamic spatial systems are also accounted for and the relevant computational tasks addressed by the proposed formalisation are stated explicitly.

This presentation focusses on the analysis and design of human-centered, embodied, cognitive user experiences from the perspectives of spatial cognition and computation, artificial intelligence, and human-computer interaction research. Focusing on large-scale built up spaces (in particular hospitals), this presentation will particularly address:

‘how can human-centered cognitive modalities of visuo-locomotive perception constitute the foundational building blocks of design education, discourse, systems, and the professional practice of spatial design for architecture’.

The presentation will emphasizeevidence-based multimodality studies from the viewpoints of visuo-locomotive (i.e., pertaining to vision, movement, and wayfinding) cognitive experiences. Modalities being investigated include: (1) visual attention (by eye-tracking), gesture, language, facial expressions; (2) human expert guided event segmentation (e.g., coming from behavioral or environmental psychologists, designers, annotators); (3) deep analysis based on dialogic components, think-aloud protocols. We demonstrate (1–3) in the context of a large-scale study conducted at the Old and New Parkland Hospitals in Dallas, Texas.

This research (and symposium) calls for a tightly integrated approach combining analytical methods (rooted in AI and computational cognition) and empirical methods (rooted in psychology and perception studies) for developing human-centered architectural design technologies, and technology-mediated (architectural) design synthesis.

In addition to six paper presentations, which will be accompanied by discussions, the workshop features two keynote speakers: Anthony Cohn (University of Leeds, UK) and Henry Kautz (University of Rochester, USA).

This symposium—conducted in two parts—explores the confluence of empirically-based qualitative research in the cognitive and psychological sciences (focusing on visual and spatial cognition) with computationally-driven analytical methods (rooted in artificial intelligence) in the service of communications, media, design, and human behavioural studies. With a focus on architecture and visuo-auditory media design, the twin-symposia will demonstrate recent results and explore the synergy of research methods for the study of human behaviour in the chosen (design) contexts of socio-cultural, and socio-technological significance.

The symposium brings together experts and addresses methodsand perspectives from:

•  Visuo-Spatial Cognition and Computation

•  Artificial Intelligence, Cognitive Systems

•  Multimodality and Interaction

•  Cognitive Science and Psychology

•  Neuroscience

•  Design Cognition and Computation

•  Communications and Media Studies

•  Architecture, Built Environment

•  Design Studies (focus on architecture and visuo-auditory media)

•  Evidence Based Design

The symposium particularly emphasises the role of multimodality and mediated interaction for the analysis and design of human-centered, embodied, cognitive user experiences in everyday life and work. Here, the focus is on multimodality studies aimed at the semantic interpretation of human behaviour, and the empirically-driven synthesis of embodied interactive experiences in real world settings. In focus are narrative media design, architecture and built environment design, product design, cognitive media studies (film, animation, VR, sound and music design), and user interaction studies. In these contexts, the symposium emphasizes evidence-based multimodality studies from the viewpoints of visual (e.g.,attention and recipient effects), visuo-locomotive (e.g. , movement, wayfinding), and visuo-auditory (e.g., narrative media) cognitive experiences. Modalities being investigated include, but are not limited to:

•  visual attention (by eye-tracking), gesture, speech, language, facial expressions, tactile interactions, olfaction, biosignals;

•  human expert guided event segmentation (e.g. coming from behavioral or environmental psychologists, designers, annotators,crowd-sensing)

•  deep analysis based on dialogic components, think-aloud protocols

The scientific agenda of the twin-symposia also emphasizes the multi-modality of the embodied visuo-spatial thinking involved in ‘‘problem-solving’’ for the design of objects, artefacts, and inter-active people-experiences emanating there from. Universality andinclusion in ‘‘design thinking’’ are of overarching focus in all design contexts relevant to the symposium; here, the implications of mul-timodality studies for inclusive design, e.g.,creation of presentations of the same content in different modalities, are also of interest. The symposium provides a platform to discuss the development of next-generation embodied interaction design systems, practices, and (human-centered) assistive frameworks and technologies encompassing the multi-faceted nature of embodied design conception and synthesis. Individual contributions/talks within the two symposia address the themes under consideration from formal, computational, cognitive, design, engineering, empirical, and philosophical perspectives.

We present recent and emerging advances in computational cognitive vision addressing artificial visual and spatial intelligence at the interface of (spatial) language, (spatial) logic and (spatial) cognition research. With a primary focus on explainable sensemaking of dynamic visuospatial imagery, we highlight the (systematic and modular) integration of methods from knowledge representation and reasoning, computer vision, spatial informatics, and computational cognitive modelling. A key emphasis here is on generalised (declarative) neurosymbolic reasoning & learning about space, motion, actions, and events relevant to embodied multimodal interaction under ecologically valid naturalistic settings in everyday life. Practically, this translates to general-purpose mechanisms for computational visual commonsense encompassing capabilities such as (neurosymbolic) semantic question-answering, relational spatio-temporal learning, visual abduction etc.

The presented work is motivated by and demonstrated in the applied backdrop of areas as diverse as autonomous driving, cognitive robotics, design of digital visuoauditory media, and behavioural visual perception research in cognitive psychology and neuroscience. More broadly, our emerging work is driven by an interdisciplinary research mindset addressing human-centred responsible AI through a methodological confluence of AI, Vision, Psychology, and (human-factors centred) Interaction Design.

Design is one of the most complex of human endeavors requiring an enormous number of often conflicting criteria to be contemplated when identifying optimal solutions. Design is constrained by guidelines, codes, and standards applicable to the specific cultural and locational context that the design will be sited. Furthermore, a design has to be created within a collaborative team consisting of many professionals focused on specific subsystems and expert preferences that provide unique functionality to the overall design. The increasing use and capability of software tools involved in the creation and processing of such spatial information has also led to elevated levels of complexity that spurred a need to structure, query and reason about multiple spatial representations of buildings and their components in new ways.

This transcript documents select parts of discus-sions on the confluence of cognition, interaction, design, and human behaviour studies. The interview and related events were held as part of the CoDesign 2017 Roundtable (Bhatt in CoDesign 2017—The Bremen Summer of Cognition and Design/CoDesign Roundtable. University of Bremen, Bremen, 2017) at the University of Bremen (Germany) in June 2017. The Q/A sessions were moderated by Mehul Bhatt (University of Bremen, Germany., and Örebro Uni-versity, Sweden) and Daniel Levin (Vanderbilt University, USA). Daniel Levin served in a dual role: as co-moderator of the discussion, as well as interviewee. The transcript is published as part of a KI Journal special issue on “Seman-tic Interpretation of Multi-Modal Human Behaviour Data” (Bhatt and Kersting in Special Issue on: Semantic Interpre-tation of Multimodal Human Behaviour Data, Artif Intell, 2017).

Ambient intelligence environments necessitate representing and reasoning about dynamic spatial scenes and configurations. The ability to perform predictive and explanatory analyses of spatial scenes is crucial towards serving a useful intelligent function within such environments. We present a formal qualitative model that combines existing qualitative theories about space with it formal logic-based calculus suited to modelling dynamic environments, or reasoning about action and change in general. With this approach, it is possible to represent and reason about arbitrary dynamic spatial environments within a unified framework. We clarify and elaborate on our ideas with examples grounded in a smart environment.

We present an approach to assist the smart environment design process by means of automated validation of work-in-progress designs. The approach facilitates validation of not only the purely structural requirements, but also the functional requirements expected of a smart environment whilst keeping in mind the plethora of sensory and interactive devices embedded within such an environment. The approach, founded in spatio-terminological reasoning, is illustrated in the context of formal ontology modeling constructs and reasoners, industrial architecture data standards and state-of-the-art commercial design software.

The use of ontologies lies at the very heart of the newly emerging era of semantic web. Ontologies provide a shared conceptualization of some domain that may be communicated between people and application systems. As information on the web increases significantly in size, web ontologies also tend to grow bigger, to such an extent that they become too large to be used in their entirety by any single application. Moreover, because of the size of the original ontology, the process of repeatedly iterating the millions of nodes and relationships to form an optimized sub-ontology becomes very computationally extensive. Therefore, it is imperative that parallel and distributed computing techniques be utilized to implement the extraction process. These problems have stimulated our work in the area of sub-ontology extraction where each user may extract optimized sub-ontologies from an existing base ontology. The extraction process consists of a number of independent optimization schemes that cover various aspects of the optimization process, such as ensuring consistency of the user-specified requirements for the sub-ontology, ensuring semantic completeness of the sub-ontology, etc. Sub-ontologies are valid independent ontologies, known as materialized ontologies, that are specifically extracted to meet certain needs. Our proposed and implemented framework for the extraction process, referred to as Materialized Ontology View Extractor (MOVE), has addressed this problem by proposing a distributed architecture for the extraction/optimization of a sub-ontology from a large-scale base ontology. We utilize coarse-grained data-level parallelism inherent in the problem domain. Such an architecture serves two purposes: (a) facilitates the utilization of a cluster environment typical in business organizations, which is in line with our envisaged application of the proposed system, and (b) enhances the performance of the computationally extensive extraction process when dealing with massively sized realistic ontologies. As ontologies are currently widely used, our proposed approach for distributed ontology extraction will play an important role in improving the efficiency of ontology-based information retrieval.

The new era of semantic web has enabled users to extract semantically relevant data from the web. The backbone of the semantic web is a shared uniform structure which defines how web information is split up regardless of the implementation language or the syntax used to represent the data. This structure is known as an ontology.

As information on the web increases significantly in size, Web ontologies also tend to grow bigger to such an extent that they become too large to be used in their entirety by any single application. This has stimulated our work in the area of sub-ontology extraction where each user may extract optimized sub-ontologies from an existing base ontology.

Sub-ontologies are valid independent ontologies, known as materialized ontologies, that are specifically extracted to meet certain needs. Because of the size of the original ontology, the process of repeatedly iterating the millions of nodes and relationships to form an optimized sub-ontology can be very extensive. Therefore we have identified the need for a distributed approach to the extraction process. As ontologies are currently widely used, our proposed approach for distributed ontology extraction will play an important role in improving the efficiency of information retrieval.

The articulation of the Science of Design by Herbert Simon and the paradigmatic relevance of Artificial Intelligence in that context are closely intertwined topics: Simon elaborates the ‘Sciences of the Artificial’ in the context of the design of artefacts. Situated in this AI-centric view of design, we characterize “spatial computing for design” as a specialisation concerned with the development of the general representational and computational apparatus necessary for solving modelling and reasoning problems in spatial design. Several representation and reasoning problems are dis-cussed in the backdrop of relevant examples involving the formal modelling of structural form with respect to a desired/anticipated artefactual function. The discussion, although applicable to any spatial design activity, is grounded in the domain of assistive decision-support in the context of a conventional computer-aided architecture design workflow.

The development of smart assistive technology for personal living and public environments is an opportunity that has been recently recognized by research labs across the world. A particular theme that has garnered attention in many countries is the problem of an aging population. The combination of a much larger elderly population and the ever increasing cost of providing full-time human care for them means that finding practical assisted living solutions for this group is becoming increasingly important. Computing is the obvious choice to provide an answer to this growing problem, but to have a real impact, computer-based assistive technologies will need to possess the ability to interact with, and interpret, the actions and situations of those they are designed to assist.

The papers in this book explore the diversity of the field of ambient intelligence, as well as the wide range of approaches and variety of applications that may prove to be possible. Consideration is given to how space, action, time, and other contexts can be represented and reasoned about for use in sensory mapping, multi-agent interactions, assisted living, and even emergency responses. Many techniques are examined; variety represents one of the most important strengths of this area, meaning that the weakness of one approach can be offset by the capability of others.

The book consists of research contributions dealing with the crucial notion of situational awareness within assistive smart systems emerging as an overarching concept. An applied computer science character has been retained, whilst bringing to the fore research projects where formal knowledge representation and reasoning techniques have been demonstrated to be applicable to areas within the broader field of ambient intelligence and smart environments.

This workshop has a special focus on the topic of spatio-temporal aspects of human activity interpretation, especially welcoming research concerned with monitoring and inter- pretation of people interactions, real-time commonsense situational awareness involving aspects such as scene perception and understanding, perceptual data analytics, and prediction and explanation-driven high-level control of autonomous systems. In this context, basic topics deemed important include activity and process models; behaviour and intention interpretation; spatial learning; modeling and reasoning about space, events, actions, interaction; spatio-temporal dynamics; and commonsense reasoning about spatio-temporal change.

Form, function and the relationship between the two serve a crucial role in design. Within architectural design, key aspects of the anticipated function of buildings, or of spatial environments in general, are supposed to be supported by their structural form, i.e., their shape, layout, or connectivity. Whereas the philosophy of form and function is a well-researched topic, the practical relations and dependencies between form and function are only known implicitly by designers and architects. Specifically, the formal modelling of structural forms and resulting artefactual functions within design and design assistance systems remains elusive.

In our work, we aim at making these definitions explicit by ontologically modelling respective domain entities, their properties and related constraints. We interpret "(structural) form" and "(artefactual) function" by specifying modular ontologies and their interplay for the architectural design domain. A key aspect in our modelling approach is the use of formal conceptual requirements and qualitative spatial calculi as a link between the structural form of a design and the differing functional capabilities that it affords or leads to. We demonstrate how our ontological modelling reflects types of architectural form and function, and how it facilitates the conceptual modelling of requirement constraints in architectural design.

We demonstrate the manner in which high-level design requirements, e.g., as they correspond to the commonsensical conceptualisation of expert designers, may be formally specified within practical information systems, wherein heterogeneous perspectives and conceptual commitments are needed. Focussing on semantics, modularity and consistency, we argue that our formalisation serves as a synergistic interface that mediates between the two disconnected domains of human abstracted qualitative/conceptual knowledge and its quantitative/precision-oriented counterpart within systems for spatial design (assistance). Our demonstration utilises simple, yet real world examples.

This special issue presents interdisciplinary research—at the interface of artificial intelligence, cogni-tive science, and human-computer interaction—focussing on the semantic interpretation of human behaviour. The special issue constitutes an attempt to highlight and steer founda-tional methods research in artificial intelligence, in particular knowledge representation and reasoning, for the develop-ment of human-centred cognitive assistive technologies. Of specific interest and focus have been application outlets for basic research in knowledge representation and reason-ing and computer vision for the cognitive, behavioural, and social sciences.

We propose CLP(QS), a declarative spatial reasoning framework capable of representing and reasoning about high-level, qualitative spatial knowledge about the world. We systematically formalize and implement the semantics of a range of qualitative spatial calculi using a system of non-linear polynomial equations in the context of a classical constraint logic programming framework. Whereas CLP(QS) is a general framework, we demonstrate its applicability for the domain of Computer Aided Architecture Design. With CLP(QS) serving as a prototype, we position declarative spatial reasoning as a general paradigm open to other formalizations, reinterpretations, and extensions. We argue that the accessibility of qualitative spatial representation and reasoning mechanisms via the medium of high-level, logic-based formalizations is crucial for their utility toward solving real-world problems.

The workshop on Multimodality in Embodied Experience Design addresses the role of multimodality and mediated interaction for the analysis and design of human-centred, embodied, cognitive user experiences. Research topics being addressed encompass formal, computational, cognitive, design, engineering, empirical, and philosophical perspectives at the interface of artificial intelligence, cognitive science, and interaction design.

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.

We propose the application of a novel sub-ontology extraction methodology for achieving interoperability and improving the semantic validity of information retrieval in the medical information systems (MIS) domain. The system offers advanced pro. ling of a user's field of specialization by exploiting the concept of sub-ontology extraction, i.e., each sub-ontology may subsequently represent a particular user pro. le. Semantic pro. ling of a user's field of specialization or interest is necessary functionality in any medical domain information retrieval system; this is because the (structural and semantic) extent of information sources is massive and individual users are only likely to be interested in specific parts of the overall knowledge documents on the basis of their area of specialization. The prototypical system, OntoMOVE, has been specifically designed for application in the medical information systems domain. OntoMOVE utilizes semantic web standards like RDF(S) and OWL in addition to medical domain standards and vocabularies encompassed by the UMLS knowledge sources.

The use of formal knowledge representation structures, or ontologies, has found immense applicability for the interoperability of software systems, e.g., alignment of software and business process models. Toward the management of such knowledge structures, an important foundational problem is that of ontology reuse - it is uncommon for new applications or for different components within one application to use an already available ontology in its entirety. Depending on component specific requirements, typical re-usages are restricted to refined versions of an existing ontology, with the refinement taking the form of a contraction of the knowledge contained therein. Furthermore, when the ontology is used to ascribe meaning to independently existing 'resources' (e.g., documents collections, source code, software manuals, process template repositories) by way of meta-data, there exists a direct mapping between different views/re-uses of an ontology and their respective semantic scopes within an annotated resource repository thereby leading to the concept of view/reuse dependent resource retrieval. We implement a framework that supports ontology reuse by way of a requirement driven sub-ontology extraction methodology. Additionally, based on this concept of a sub-ontology, we implement the idea of a user/component 'requirement profile' consisting of semantic descriptions of the user's interest within a 'resource repository' that has been annotated with semantic types from the ontology under consideration. A generic framework that implements these ideas and its application in the domains of Medical Information Retrieval systems and Business Process Management Systems (BPMS) is presented.

We propose the utilisation of a general formalism to reason about action & change for reasoning about the dynamic purpose-directed aspects of spatial change. Such an approach is necessary toward the general integration of qualitative spatial reasoning with reasoning about the teleological aspects of spatial change. With this as the overall context, the main contribution of this paper is to illustrate first ideas relevant to providing a causal perspective to qualitative spatial reasoning using the situation calculus. With minimal notions about space & spatial dynamics, we perform a naive characterisation of objects based on their physical properties and investigate the key representational aspects of a topological theory of space, namely the region connection calculus, in the situation calculus. Further, ontological distinctions are made between various occurrents, i.e., actions and internal & external events, and a domain level characterisation of spatial occurrents in terms of their spatial pre-conditions & effects is performed so as to provide a causal perspective to spatial reasoning.

Qualitative spatial representation and reasoning has emerged as a major sub-field of AI in the past decade. An important research problem within the field is that of integrated reasoning about various spatial aspects such as distance, size, topology etc - an important application here being the qualitative simulation of physical processes. Approaches based on topology alone fail to provide an explicit account of other important aspects of spatial change thereby also not utilizing dynamically available information pertaining to them. Our work in this paper is based on the idea that a general theory of spatial simulation based on topological changes alone can be enriched by the inclusion of sub-theories relevant to other aspects of spatial change. We propose a general framework consisting of dynamic constraints for the enrichment of a topological theory of spatial changes. We propose the utilisation of such dynamic constraints for the incorporation of dynamically available information relevant to various aspects of space thereby making that aspect explicit in the theory. As an example of the proposed approach, we integrate dynamically available information pertaining to motion and size with the topological theory of RCC-8 using our framework of dynamic constraints.

We use a qualitative theory of spatial change and illustrate some of the key representational aspects of specifying such a theory using a formalism to reason about action & change; an effort that we regard to be essential toward a general integration of qualitative spatial reasoning with reasoning about the dynamic, causal aspects of spatial change. A topological theory of space, namely the region connection calculus, is used as the spatial metaphor in this work; the reason here primarily being that topological distinctions are inherently qualitative in nature and also because a relational approach as general as the RCC is representative of a similar class of relational techniques in the QSR domain. As such, our results can be easily generalised over a wide range of calculi, encompassing other aspects of space, that are based on similar semantics. The main aim of this paper is to illustrate first ideas on how a causal perspective to qualitative spatial reasoning may be provided using the situation calculus, which is a formalism to reason about dynamically changing domains, The minimalist notions of space and/or spatial dynamics in this paper are based on the hypothesis that it is imperative to approach the problem of the said integration at a elementary level before a higher-level abstraction involving complex actions & events is developed.

The simulation of the behaviour of autonomous entities in space is an interesting research method to advance our understanding of the interaction of human beings with the environment. Although rather complex cognitive models of human-level Situation Awareness (SA) in dynamic environments exist, computational approaches to represent the same remain at best ad-hoc - cognitively inadequate or bearing little or no resemblance to the qualitative manner in which humans seemingly represent & reason about knowledge. The aim of our research is to investigate the computational aspects of situation awareness of autonomous entities in large-scale simulated spaces, called Synthetic Environments (SE). This is done within the scope of an understanding of situation awareness that encompasses common-sense conceptual reasoning and integrated qualitative reasoning about space, time & causality As a product of our research, we envisage to develop a logic based computational framework based on a unified representational semantics for space, time & causality - the essence of which is a process model involving abstract ontological commitments involving spatial, temporal and action event oriented concepts, alongwith a capability to handle concurrent and continuous phenomena. The framework, which is representative of our model of situation awareness, will be most beneficial for systems involving the representation of physical and/or intelligent autonomous processes. However, as an exemplar of our approach, we are interested in applying the framework for the representation of autonomous behaviour in defence Modelling & Simulation (M&S) applications.

The application of Ontologies for the definition and interoperability of complementary taxonomies has been well-recognised within the Modelling & Simulation (M&S) community. Our research pertaining to the specification of Synthetic Environment (SE) representational semantics has proposed the use of an Synthetic Environment Data Representation Ontology (sedOnto), which is modeled using W3C ' s Web Ontology Language(OWL), The vocabulary specified in sedOnto is based the SEDRIS Data Representation Model (DRM), which is a technological framework for SE data interchange and interoperability. In this paper, we present STOWL - SEDRIS To OWL Transform that automates the transformation of a SEDRIS based SE to a Web-Ontology based representation scheme in the OWL language. The target representation scheme, which shall be based on sedOnto, is in actuality an instantiation of the SE data representation terminology as specified by sedOnto. Such a transformation has many perceived advantages: It enhances SE interoperability by utilizing a Web-Ontology based approach for the specification of SE representation data, is consistent with existing industry based SE representation standards, namely SEDRIS, and that the representation scheme facilitates ontological reasoning over SE objects; a facility that is not directly supported by the SEDRIS DRM.

When undertaking the task of design, architects imagine and anticipate the visuospatial and navigational experience of building users during the initial design conception phase. The ultimate goal is to ensure that the final physical built-up structure inherently performs with respect to people-centered design criteria encompassing function, behavior, and affordance. We argue that next-generation people-centered design systems, frameworks, assistive tools, educational discourse, and design policies and practices need to be explicitly founded on the cognitive modalities of human perception, attention, action, dynamics, environmental affordance and user experience, and design conception and semantics. We posit that this requires a holistic approach to architectural design cognition, encompassing the application of principles, practices, and methods from the fields of architecture and engineering, cognitive science, spatial cognition and computation, and evidence-based empirical methods in environmental and social psychology.

We propose a human-centred model for abstraction, modelling and computing in function-driven spatial design for architecture. The primitive entities oour design conception ontology and computing framework are driven by classic notions of structure, function, and a↵ordance in design, and are directly based on the fundamental human perceptual and analytical modalities of visual and locomotive exploration of space. With an emphasis on design semantics, our model for spatial design marks a fundamental shift from contemporary modelling and computational foundations underlying engineering- centred computer aided design systems. We demonstrate the application of our model within a system for human-centred compu- tational design analysis and simulation. We also illustrate the manner in which our design modelling and computing framework seamlessly builds on contemporary industry data modelling standards within the architecture and construction informatics communities.

This chapter is about ‘space’: empty space, spatial structures, and the process of structuring. We organize empty space by building-up structures and artefacts of our everyday existence. This structuring transforms empty space into something of a desired form (e.g. a balanced room, a visually pleasing scene), function (e.g. easily navigable), and semantic connotation (e.g. of a ‘place’). The chapter is written from the perspective of spatial informatics and addresses space at the scale of everyday human perception and thinking. The core of this chapter is to present the informatics of spatial structure; this is done at three levels: (1) the conception of structural form, as it accrues in the minds of people, and its expression, using spatio-linguistic modalities; (2) the formalization of space, using representational means for spatial abstraction; and (3) the computation of structural forms in a manner that constructively assures, assists, and empowers those who conceive of those forms. The chapter is grounded to reality with respect to a particular class of spatial assistance systems, e.g. for spatial design, where our interpretations of creative and constructive assistance are applicable. We also present case studies in domains such as design creativity for media pre-production, and real-time emergency assistance, though architectural design remains an area of special emphasis throughout the chapter.

We propose a human-centred model for abstraction, modelling and computing in function-driven spatial design for architecture. The primitive entities of our design conception ontology and computing framework are driven by classic notions of structure, function, and affordance in design, and are directly based on the fundamental human perceptual and analytical modalities of visual and locomotive exploration of space.

With an emphasis on design semantics, our model for spatial design marks a fundamental shift from contemporary modelling and computational foundations underlying engineering-centred computer aided design systems. We demonstrate the application of our model within a system for human-centred computational design analysis and simulation. We also illustrate the manner in which our design modelling and computing framework seamlessly builds on contemporary industry data modelling standards within the architecture and construction informatics communities.

We present computational visuo-spatial representation and reasoning from the viewpoint of the research areas of artificial intelligence, spatial cognition and computation, and human-computer interaction. The particular focus is on demonstrating recent advances in the theory and practice of spatial reasoning, and its significance and potential as a foundational AI method for (intelligent) computational cinematography & editing systems.

We present a cognitive design assistance system equipped with analytical capabilities aimed at anticipating architectural building design performance with respect to peoplecentred functional design goals. The paper focuses on the system capability to generate narratives of visuo-locomotive user experience from digital computer-aided architecture design (CAAD) models. The system is based on an underlying declarative narrative representation and computation framework pertaining to conceptual, geometric, and qualitative spatial knowledge. The semantics of the declarative narrative model, i.e., the overall representation and computation model, is founded on: (a) conceptual knowledge formalised in an OWL ontology; (b) a general spatial representation and reasoning engine implemented in constraint logic programming; and (c) a declaratively encoded (narrative) construction process (based on search over graph structures) implemented in answer-set programming.

We emphasise and demonstrate: complete system implementation, scalability, and robust performance & integration with industry-scale architecture industry tools (e.g., Revit, Archi-CAD) & standards (BIM, IFC).

We address computational cognitive vision and perception at the interface of language, logic, cognition, and artificial intelligence. The chapter presents general methods for the processing and semantic interpretation of dynamic visuospatial imagery with a particular emphasis on the ability to abstract, learn, and reason with cognitively rooted structured characterisations of commonsense knowledge pertaining to space and motion. The presented work constitutes a systematic model and methodology integrating diverse, multi-faceted AI methods pertaining Knowledge Representation and Reasoning, Computer Vision, and Machine Learning towards realising practical, human-centred artificial visual intelligence.

Semantic interpretation of dynamic visuospatial imagery calls for a general and systematic integration of methods in knowledge representation and computer vision. Towards this, we highlight research articulating & developing deep semantics, characterised by the existence of declarative models –e.g., pertaining space and motion– and corresponding formalisation and reasoning methods sup- porting capabilities such as semantic question-answering, relational visuospatial learning, and (non-monotonic) visuospatial explanation. We position a working model for deep semantics by highlighting select recent / closely related works from IJCAI, AAAI, ILP, and ACS. We posit that human-centred, explainable visual sensemaking necessitates both high-level semantics and low-level visual computing, with the highlighted works providing a model for systematic, modular integration of diverse multifaceted techniques developed in AI, ML, and Computer Vision.

Evidence-based design (EBD) for architecture involves the study of post-occupancy behaviour of building users with the aim to provide an empirical basis for improving building performance [Hamilton and Watkins 2009]. Within EBD, the high-level, qualitative analysis of the embodied visuo-locomotive experience of representative groups of building users (e.g., children, senior citizens, individuals facing physical challenges) constitutes a foundational approach for understanding the impact of architectural design decisions, and functional building performance from the viewpoint of areas such as environmental psychology, wayfinding research, human visual perception studies, spatial cognition, and the built environment [Bhatt and Schultz 2016].

We position a narrative-centred computational model for high-level knowledge representation and reasoning in the context of a range of assistive technologies concerned with visuo-spatial perception and cognition tasks. Our proposed narrative model encompasses aspects such as space, events, actions, change, and interaction from the viewpoint of commonsense reasoning and learning in large-scale cognitive systems. The broad focus of this paper is on the domain of human-activity interpretation in smart environments, ambient intelligence etc. In the backdrop of a smart meeting cinematography domain, we position the proposed narrative model, preliminary work on perceptual narrativisation, and the immediate outlook on constructing general-purpose open-source tools for perceptual narrativisation.

The evidence-based analysis of people's navigation and wayfinding behaviour in large-scale built-up environments (e.g., hospitals, airports) encompasses the measurement and qualitative analysis of a range of aspects including people's visual perception in new and familiar surroundings, their decision-making procedures and intentions, the affordances of the environment itself, etc. In our research on large-scale evidence-based qualitative analysis of wayfinding behaviour, we construe visual perception and navigation in built-up environments as a dynamic narrative construction process of movement and exploration driven by situation-dependent goals, guided by visual aids such as signage and landmarks, and influenced by environmental (e.g., presence of other people, time of day, lighting) and personal (e.g., age, physical attributes) factors. We employ a range of sensors for measuring the embodied visuo-locomotive experience of building users: eye-tracking, egocentric gaze analysis, external camera based visual analysis to interpret fine-grained behaviour (e.g., stopping, looking around, interacting with other people), and also manual observations made by human experimenters. Observations are processed, analysed, and integrated in a holistic model of the visuo-locomotive narrative experience at the individual and group level. Our model also combines embodied visual perception analysis with analysis of the structure and layout of the environment (e.g., topology, routes, isovists) computed from available 3D models of the building. In this framework, abstract regions like the visibility space, regions of attention, eye movement clusters, are treated as first class visuo-spatial and iconic objects that can be used for interpreting the visual experience of subjects in a high-level qualitative manner. The final integrated analysis of the wayfinding experience is such that it can even be presented in a virtual reality environment thereby providing an immersive experience (e.g., using tools such as the Oculus Rift) of the qualitative analysis for single participants, as well as for a combined analysis of large group. This capability is especially important for experiments in post-occupancy analysis of building performance. Our construction of indoor wayfinding experience as a form of moving image analysis centralizes the role and influence of perceptual visuo-spatial characteristics and morphological features of the built environment into the discourse on wayfinding research. We will demonstrate the impact of this work with several case-studies, particularly focussing on a large-scale experiment conducted at the New Parkland Hospital in Dallas Texas, USA.

High-level semantic interpretation of (dynamic) visual imagery calls for general and systematic methods integrating techniques in knowledge representation and computer vision. Towards this, we position "deep semantics", denoting the existence of declarative models –e.g., pertaining "space and motion"– and corresponding formalisation and methods supporting (domain-independent) explainability capabilities such as semantic question-answering, relational (and relationally-driven) visuospatial learning, and (non-monotonic) visuospatial abduction. Rooted in recent work, we summarise and report the status quo on deep visuospatial semantics —and our approach to neurosymbolic integration and explainable visuo-spatial computing in that context— with developed methods and tools in diverse settings such as behavioural research in psychology, art & social sciences, and autonomous driving.

The modeling, analysis and visualization of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about space, events, actions and change. With this as a basis and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solution techniques chiefly involving qualitative abstraction, data integration and spatial consistency and practical geospatial abduction.