The relationship between knowledge,belief, and certainty

We consider the relation between knowledge and certainty, where a fact isknown if it is true at all worlds an agent considers possible and iscertain if it holds with probability 1. We identify certainty with belief, interpreted probabilistically. We show that if we assume one fixed probability assignment, then the logic KD45, which has been identified as perhaps the most appropriate for belief, provides a complete axiomatization for reasoning about certainty. Just as an agent may believe a fact although is false, he may be certain that a fact is true although is false. However, it is easy to see that an agent can have such false (probabilistic) beliefs only at a set of worlds of probability 0. If we restrict attention to structures where all worlds have positive probability, then S5 provides a complete axiomatization. If we consider a more general setting, where there might be a different probability assignment at each world, then by placing appropriate conditions on thesupport of the probability function (the set of worlds which have non-zero probability), we can capture many other well-known modal logics, such as T and S4. Finally, we considerMiller's principle, a well-known principle relating higher-order probabilities to lower-order probabilities, and show that in a precise sense KD45 characterizes certainty in those structures satisfying Miller's principle.     

Toward an engineering science of knowledge-based design

In this paper, we present a framework for organizing, evaluating, and developing knowledge-based models of the design process. We argue that evaluation of a design process model can be carried out from three usefully distinguished perspectives: the knowledge it embodies; the functionality of the design process, from a problem-solving viewpoint; and the implementation of the design process as an actual program. This paper focuses on the first two perspective. We systematically introduce a set of basic functional components, and show how existing approaches or systems can be viewed as configurations of these components, in which domain knowledge has been incorporated. As we lay out this framework, we illustrate it in a simple way by using it to describe knowledge-based house floorplanners. We then complete our presentation by analysing a more complex knowledge-based system (DONTE) that designs circuits.     

VIVACE: A framework for the systematic evaluation of variability support in process-aware information systems

ContextThe increasing adoption of process-aware information systems (PAISs) such as workflow management systems, enterprise resource planning systems, or case management systems, together with the high variability in business processes (e.g., sales processes may vary depending on the respective products and countries), has resulted in large industrial process model repositories. To cope with this business process variability, the proper management of process variants along the entire process lifecycle becomes crucial.ObjectiveThe goal of this paper is to develop a fundamental understanding of business process variability. In particular, the paper will provide a framework for assessing and comparing process variability approaches and the support they provide for the different phases of the business process lifecycle (i.e., process analysis and design, configuration, enactment, diagnosis, and evolution).MethodWe conducted a systematic literature review (SLR) in order to discover how process variability is supported by existing approaches.ResultsThe SLR resulted in 63 primary studies which were deeply analyzed. Based on this analysis, we derived the VIVACE framework. VIVACE allows assessing the expressiveness of a process modeling language regarding the explicit specification of process variability. Furthermore, the support provided by a process-aware information system to properly deal with process model variants can be assessed with VIVACE as well.ConclusionsVIVACE provides an empirically-grounded framework for process engineers that enables them to evaluate existing process variability approaches as well as to select that variability approach meeting their requirements best. Finally, it helps process engineers in implementing PAISs supporting process variability along the entire process lifecycle.     

Designing multi-agent unit tests using systematic test design patterns-(extended version)

Software agents are the basic building blocks in many software systems especially those based on artificial intelligence methods, e.g., reinforcement learning based multi-agent systems (MASs). However, testing software agents is considered a challenging problem. This is due to the special characteristics of agents which include its autonomy, distributed nature, intelligence, and heterogeneous communication protocols. Following the test-driven development (TDD) paradigm, we present a framework that allows MAS developers to write test scenarios that test each agent individually. The framework relies on the concepts of building mock agents and testing common agent interaction design patterns. We analyze the most common agent interaction patterns including pair and mediation patterns in order to provide stereotype implementation for their corresponding test cases. These implementations serve as test building blocks and are provided as a set of ready-for-reuse components in our repository. This way, the developer can concentrate on testing the business logic itself and spare him/her the burden of implementing tests for the underlying agent interaction patterns. Our framework is based on standard components such as the JADE agent platform, the JUnit framework, and the eclipse plug-in architecture. In this paper, we present in details the design and function of the framework. We demonstrate how we can use the proposed framework to define more stereotypes in the code repository and provide a detailed analysis of the code coverage for our designed stereotype test code implementations.     

Hyperintensions

Standard possible worlds semantics has been known from the startto have a problem with granularity: for a wide range of natural-language(NL) entailment patterns, not enough meaning distinctions areavailable to make predictions consistent with robust intuitions.Though numerous solutions have been proposed, often of greatingenuity and technical sophistication, none of these has gainedwidespread acceptance. As a result, most semanticists have madea practical decision to work in a framework known to have dubiousfoundations and leave the foundational problems to mathematicallogicians. Here, a new approach is proposed which may be simpleenough and conservative enough to be practical for working empiricaland computational semanticists. More specifically, I show howthe use of a higher-order logic with definable subtypes leadsto a novel and surprisingly straightforward solution of thegranularity problem. I also call attention to a hitherto unnoticedproblem in standard approaches to NL semantics having to dowith non-principal ultrafilters and show why it does not ariseunder my proposal. The two main technical innovations that drivethe proposal are (i) axiomatizing NL entailment as a preorder(as opposed to an order) on the set of (primitive) propositions,and (ii) defining worlds as certain sets of propositions (viz.ultrafilters). These innovations provide just the tools we needto develop a formally explicit theory of hyperintensions, ¹mathematical models of Fregean senses of a finer granularitythan the familiar intensions (functions to extensions from worlds,where the worlds in turn are theoretical primitives) of mainstreamKripke/Montague-inspired NL semantics.     

A declarative approach to procedural modeling of virtual worlds

With the ever increasing costs of manual content creation for virtual worlds, the potential of creating it automatically becomes too attractive to ignore. However, for most designers, traditional procedural content generation methods are complex and unintuitive to use, hard to control, and generated results are not easily integrated into a complete and consistent virtual world.We introduce a novel declarative modeling approach that enables designers to concentrate on stating what they want to create instead of on describing how they should model it. It aims at reducing the complexity of virtual world modeling by combining the strengths of semantics-based modeling with manual and procedural approaches. This article describes two of its main contributions to procedural modeling of virtual worlds: interactive procedural sketching and virtual world consistency maintenance. We discuss how these techniques, integrated in our modeling framework SketchaWorld, build up to enable designers to create a complete 3D virtual world in minutes. Procedural sketching provides a fast and more intuitive way to model virtual worlds, by letting designers interactively sketch their virtual world using high-level terrain features, which are then procedurally expanded using a variety of integrated procedural methods. Consistency maintenance guarantees that the semantics of all terrain features is preserved throughout the modeling process. In particular, it automatically solves conflicts possibly emerging from interactions between terrain features.We believe that these contributions together represent a significant step towards providing more user control and flexibility in procedural modeling of virtual worlds. It can therefore be expected that by further reducing its complexity, virtual world modeling will become accessible to an increasingly broad group of users.     

Understanding digital transformation: A review and a research agenda

Extant literature has increased our understanding of specific aspects of digital transformation, however we lack a comprehensive portrait of its nature and implications. Through a review of 282 works, we inductively build a framework of digital transformation articulated across eight building blocks. Our framework foregrounds digital transformation as a process where digital technologies create disruptions triggering strategic responses from organizations that seek to alter their value creation paths while managing the structural changes and organizational barriers that affect the positive and negative outcomes of this process. Building on this framework, we elaborate a research agenda that proposes [1] examining the role of dynamic capabilities, and [2] accounting for ethical issues as important avenues for future strategic IS research on digital transformation.     

Formalizing the repair process — extended report

This paper defines the model-based diagnosis and repair process. We consider repair (i.e. restoration of specified system purposes) as the main goal of this process. Our goal is to define how an intelligent agent integrates and schedules observations and actions in an interleaved way in order to guarantee a specifiedsystem purpose. We define a temporal framework where all concepts necessary to represent repair (actual, possible and plausible worlds, purpose, observations, actions and failures) can be integrated. Using these concepts we present an algorithm scheme describing the repair process.Most of this work was carried out while the author was a member of the Christian Doppler Laboratory for Expert Systems     

From Technology to Communication: Psycho-social Issues in Developing Virtual Environments

Virtual reality (VR) can be considered as the leading edge of a general evolution of present communication interfaces, one whose main characteristic is the full immersion of the human sensorimotor channels into a vivid and global communication experience. By analyzing VR as a communication tool this paper tries to outline a psycho-social framework for the development and tuning of VR systems. In particular, the author identifies two key characteristics of satisfying virtual environments:disappearance of mediation—a level of experience where both the VR system and the physical environment disappear from the user's phenomenal awareness—and thesense of communitydeveloped by interaction. Social and psychological consequences of this approach are discussed, both for single- and multi-user virtual worlds.     

Measuring prevalence of other-oriented transactive contributions using an automated measure of speech style accommodation

This paper contributes to a theory-grounded methodological foundation for automatic collaborative learning process analysis. It does this by illustrating how insights from the social psychology and sociolinguistics of speech style provide a theoretical framework to inform the design of a computational model. The purpose of that model is to detect prevalence of an important group knowledge integration process in raw speech data. Specifically, this paper focuses on assessment of transactivity in dyadic discussions, where a transactive contribution is operationalized as one where reasoning is made explicit, and where that reasoning builds on a prior reasoning statement within the discussion. Transactive contributions can be either self-oriented, where the contribution builds on the speaker’s own prior contribution, or other-oriented, where the contribution builds on a prior contribution of a conversational partner. Other-oriented transacts are particularly central to group knowledge integration processes. An unsupervised Dynamic Bayesian Network model motivated by concepts from Speech Accommodation Theory is presented and then evaluated on the task of estimating prevalence of other-oriented transacts in dyadic discussions. The evaluation demonstrates a significant positive correlation between an automatic measure of speech style accommodation and prevalence of other-oriented transacts (R?=?.36, p?<?.05).     

SLurtles: Supporting constructionist learning in Second Life

Constructionism places an emphasis on the process of constructing shareable artefacts. Many virtual worlds, such as Second Life, provide learners with tools for the construction of objects and hence may facilitate in-world constructionist learning experiences. However, the construction tools available present learners with a significant barrier (or ‘high-floor’) for the novice to first master. To address this problem, this paper presents the design concepts, first implementation and analysis of SLurtles (programmable turtles in Second Life), easy-to-use, programmable construction tools for use in Second Life. During a pilot study 24 postgraduate learners in pairs and working at distance from one another, programmed SLurtles to create interactive installations in Second Life over four weeks. Open interviews were conducted, chat logs recorded and learners artefacts and reflections were collected and analysed using qualitative methods. Findings show that SLurtles provide learners with a programmable, low-floor, high-ceiling and wide-wall construction tool, which supported their construction of a wide range of complex artefacts as part of a constructionist learning experience in Second Life.     

Analyzing the dynamics of stigmergetic interactions through pheromone games

The concept of stigmergy provides a simple framework for interaction and coordination in multi-agent systems. However, determining the global system behavior that will arise from local stigmergetic interactions is a complex problem. In this paper we propose to use Game Theory to analyze stigmergetic interactions. We show that a system where agents coordinate by sharing local pheromone information can be approximated by a limiting pheromone game in which different pheromone vectors represent player strategies. This game view allows us to use established methods and solution concepts from game theory to describe the properties of stigmergy based systems. Our goal is to provide a new framework to aid in the understanding and design of pheromone interactions. We demonstrate how we can use this system to determine the long term system behavior of a simple pheromone model, by analyzing the convergence properties of the pheromone update rule in the approximating game. We also apply this model to cases where multiple colonies of agents concurrently optimize different objectives. In this case a limiting colony game can be linked to colony level interactions to characterize the global system behavior.     

The design space of dynamic interactive virtual environments

Virtual environments have become a key component of many fields and the critical component of virtual reality applications. Due to their virtual nature, they can accommodate an infinite number of possibilities. A theoretical work is presented, which decomposes those innumerous possibilities into concepts to help clarify the vast design space and provide insights into future applied research. We propose that what makes environments interesting and engaging is having worlds that are both active and reactive. This article explores the manifestations of those actions and reactions in what we term: dynamic components and interactions. We term worlds containing these dynamic interactive virtual environments (DIVE). An analysis of each component time was performed, with the purpose of providing a theoretical understanding of the respective design spaces. Initially, we collected the myriad possibilities of each component, e.g., the possible kinds of interactions. We point to examples throughout the field to ground and explain concepts presented. We then categorized of each area into taxonomies. The result of the analyses provides insights into the design space of virtual environments, exposes several avenues of research that are yet underexplored, and provides better understandings of ways in which DIVE creation can be supported.     

Information systems development: a perspective on the challenge of evolutionary complexity

This conceptual paper proposes that the methodical approach to information system development leads us to design systems that are unable to deal with the challenge of evolutionary complexity. This is examined through the use of a systemic framework that describes evolutionary complexity in terms of interaction between the concepts of distinction/connection and variation/selection. In applying these concepts to the social world we are led to conclude (a) that social regularities are emergent and not a priori given and (b) that these emergent regularities are constantly shifting and evolving. This has strong implications for the methodical approach to development, which we argue assumes social structures, mechanisms and processes as ‘invariant regularities’ that only have to be revealed to be understood. This difference leads methodical development to produce static systems that have to work in a dynamic world. The paper concludes by outlining a proposition in response to the challenge of evolutionary complexity, one where design is considered as an inherently ongoing process.     

Tornado: A self-reconfiguration control system for core-based multiprocessor CSoPCs

In this work we present a self-reconfiguration control focused on multiprocessor core-based systems implemented on FPGA technology. An infrastructure of signals, protocols, interfaces and a controller is exposed to perform safe hardware/software reconfigurations. This infrastructure is part of the Tornado framework that includes other elements such as a multi-context assembler for a reconfigurable processor or a custom design flow developed for the Wishbone IP-Core interconnection specification. We present two applications where the presented control system has been applied, and it is compared with other available approaches.     

Continuous visible k nearest neighbor query on moving objects

A visible k nearest neighbor (Vk NN) query retrieves k objects that are visible and nearest to the query object, where “visible” means that there is no obstacle between an object and the query object. Existing studies on the Vk NN query have focused on static data objects. In this paper we investigate how to process the query on moving objects continuously. We propose an effective filtering-and-refinement framework for evaluating this type of queries. We exploit spatial proximity and visibility properties between the query object and data objects to prune search space under this framework. A detailed cost analysis and a comprehensive experimental study are conducted on the proposed framework. The results validate the effectiveness of the pruning techniques and verify the efficiency of the proposed framework. The proposed framework outperforms a straightforward solution by an order of magnitude in terms of both communication and computation costs.     

SMashQ: spatial mashup framework for k-NN queries in time-dependent road networks

The k-nearest-neighbor (k-NN) query is one of the most popular spatial query types for location-based services (LBS). In this paper, we focus on k-NN queries in time-dependent road networks, where the travel time between two locations may vary significantly at different time of the day. In practice, it is costly for a LBS provider to collect real-time traffic data from vehicles or roadside sensors to compute the best route from a user to a spatial object of interest in terms of the travel time. Thus, we design SMashQ, a server-side spatial mashup framework that enables a database server to efficiently evaluate k-NN queries using the route information and travel time accessed from an external Web mapping service, e.g., Microsoft Bing Maps. Due to the expensive cost and limitations of retrieving such external information, we propose three shared execution optimizations for SMashQ, namely, object grouping, direction sharing, and user grouping, to reduce the number of external Web mapping requests and provide highly accurate query answers. We evaluate SMashQ using Microsoft Bing Maps, a real road network, real data sets, and a synthetic data set. Experimental results show that SMashQ is efficient and capable of producing highly accurate query answers.     

Managing dynamic CSPs with preferences

We present a new framework, managing Constraint Satisfaction Problems (CSPs) with preferences in a dynamic environment. Unlike the existing CSP models managing one form of preferences, ours supports four types, namely: unary and binary constraint preferences, composite preferences and conditional preferences. This offers more expressive power in representing a wide variety of dynamic constraint applications under preferences and where the possible changes are known and available a priori. Conditional preferences allow some preference functions to be added dynamically to the problem, during the resolution process, if a given condition on some variables is true. A composite preference is a higher level of preference among the choices of a composite variable. Composite variables are variables whose possible values are CSP variables. In other words, this allows us to represent disjunctive CSP variables. The preferences are viewed as a set of soft constraints using the fuzzy CSP framework. Solving constraint problems with preferences consists in finding a solution satisfying all the constraints while optimizing the global preference value. This is handled by four variants of the branch and bound algorithm, we propose in this paper, and where constraint propagation is used to improve the time efficiency in practice. In order to evaluate and compare the performance of these four strategies, we conducted an experimental study on randomly generated dynamic CSPs with quantitative preferences. The results are reported and discussed in the paper.