Staging Transformations for Multimodal Web Interaction Management

Multimodal interfaces are becoming increasingly ubiquitous with the advent of mobile devices, accessibility considerations, and novel software technologies that combine diverse interaction media. In addition to improving access and delivery capabilities, such interfaces enable flexible and personalized dialogs with websites, much like a conversation between humans. In this paper, we present a software framework for multimodal web interaction management that supports mixed-initiative dialogs between users and websites. A mixed-initiative dialog is one where the user and the website take turns changing the flow of interaction. The framework supports the functional specification and realization of such dialogs using staging transformations -- a theory for representing and reasoning about dialogs based on partial input. It supports multiple interaction interfaces, and offers sessioning, caching, and co-ordination functions through the use of an interaction manager. Two case studies are presented to illustrate the promise of this approach.Comment: Describes framework and software architecture for multimodal web interaction managemen

A Novel Way of Using Simulations to Support Urban Security Operations

The growing importance of security operations in urban terrain has triggered many attempts to address the perceived gaps in the readiness of security forces for this type of combat. One way to tackle the problem is to employ simulation techniques. Simulations are widely used to support both mission rehearsal and mission analysis, but these two applications tend to be seen as distinctly separate. We argue that integrating them in a unified framework can bring significant benefits for end-users. We perform a structured walk-through of such a unified system, in which a novel approach to integration through the behaviour cloning enabled the system to capture the operational knowledge of security experts, which is often difficult to express verbally. This capability emerged as essential for the operation of the integrated system. We also illustrate how the interplay between the system components for the mission analysis and mission rehearsal is realized

Discovering Strategic Behaviour of Multi-Agent Systems in Adversary Settings

Can specific behaviour strategies be induced from low-level observations of two adversary groups of agents with limited domain knowledge? This paper presents a domain-independent Multi-Agent Strategy Discovering Algorithm (MASDA), which discovers strategic behaviour patterns of a group of agents under the described conditions. The algorithm represents the observed multi-agent activity as a graph, where graph connections correspond to performed actions and graph nodes correspond to environment states at action starts. Based on such data representation, the algorithm applies hierarchical clustering and rule induction to extract and describe strategic behaviour. The discovered strategic behaviour is represented visually as graph paths and symbolically as rules. MASDA was evaluated on RoboCup. Both soccer experts and quantitative evaluation confirmed the relevance of the discovered behaviour patterns

Emerging from the MIST: A Connector Tool for Supporting Programming by Non-programmers

Software development is an iterative process. As user re-quirements emerge software applications must be extended to support the new requirements. Typically, a programmer will add new code to an existing code base of an application to provide a new functionality. Previous research has shown that such extensions are easier when application logic is clearly separated from the user interface logic. Assuming that a programmer is already familiar with the existing code base, the task of writing the new code can be considered to be split into two sub-tasks: writing code for the application logic; that is, the actual functionality of the application; and writing code for the user interface that will expose the functionality to the end user. The goal of this research is to reduce the effort required to create a user interface once the application logic has been created, toward supporting scientists with minimal pro-gramming knowledge to be able to create and modify pro-grams. Using a Model View Controller based architecture, various model components which contain the application logic can be built and extended. The process of creating and extending the views (user interfaces) on these model components is simplified through the use of our Malleable Interactive Software Toolkit (MIST), a tool set an infrastructure intended to simplify the design and extension of dynamically reconfigurable interfaces. This paper focuses on one tool in the MIST suite, a connec-tor tool that enables the programmer to evolve the user interface as the application logic evolves by connecting related pieces of code together; either through simple drag-and-drop interactions or through the authoring of Python code. The connector tool exemplifies the types of tools in the MIST suite, which we expect will encourage collabora-tive development of applications by allowing users to inte-grate various components and minimizing the cost of de-veloping new user interfaces for the combined compo-nents

Cognitive Activity Support Tools: Design of the Visual Interface

This dissertation is broadly concerned with interactive computational tools that support the performance of complex cognitive activities, examples of which are analytical reasoning, decision making, problem solving, sense making, forecasting, and learning. Examples of tools that support such activities are visualization-based tools in the areas of: education, information visualization, personal information management, statistics, and health informatics. Such tools enable access to information and data and, through interaction, enable a human-information discourse. In a more specific sense, this dissertation is concerned with the design of the visual interface of these tools. This dissertation presents a large and comprehensive theoretical framework to support research and design. Issues treated herein include interaction design and patterns of interaction for cognitive and epistemic support; analysis of the essential properties of interactive visual representations and their influences on cognitive and perceptual processes; an analysis of the structural components of interaction and how different operational forms of interaction components affect the performance of cognitive activities; an examination of how the information-processing load should be distributed between humans and tools during the performance of complex cognitive activities; and a categorization of common visualizations according to their structure and function, and a discussion of the cognitive utility of each category. This dissertation also includes a chapter that describes the design of a cognitive activity support tool, as guided by the theoretical contributions that comprise the rest of the dissertation. Those that may find this dissertation useful include researchers and practitioners in the areas of data and information visualization, visual analytics, medical and health informatics, data science, journalism, educational technology, and digital games

Conducting A/B Experiments with a Scalable Architecture

A/B experiments are commonly used in research to compare the effects of changing one or more variables in two different experimental groups - a control group and a treatment group. While the benefits of using A/B experiments are widely known and accepted, there is less agreement on a principled approach to creating software infrastructure systems to assist in rapidly conducting such experiments. We propose a four-principle approach for developing a software architecture to support A/B experiments that is domain agnostic and can help alleviate some of the resource constraints currently needed to successfully implement these experiments: the software architecture (i) must retain the typical properties of A/B experiments, (ii) capture problem solving activities and outcomes, (iii) allow researchers to understand the behavior and outcomes of participants in the experiment, and (iv) must enable automated analysis. We successfully developed a software system to encapsulate these principles and implement it in a real-world A/B experiment