Marc Spraragen

An intelligent assistant for interactive workflow composition

Complex applications in many areas, including scientific computations and business-related web services, are created from collections of components to form computational workflows. In many cases end users have requirements and preferences that depend on how the workflow unfolds, and that cannot be specified beforehand. Workflow editors enable users to formulate workflows, but the editors need to be augmented with intelligent assistance in order to help users in several key aspects of the task, namely: 1) keeping track of detailed constraints across selected components and their connections; 2) specifying the workflow flexibly, e.g., top-down, bottom-up, from requirements, or from available data; and 3) taking partial or incomplete descriptions of workflows and understanding the steps needed for their completion. We present an approach that combines knowledge bases (that have rich representations of components) together with planning techniques (that can track the relations and constraints among individual steps). We illustrate the approach with an implemented system called CAT (Composition Analysis Tool) that analyzes workflows and generates error messages and suggestions in order to help users compose complete and consistent workflows.

Simplifying construction of complex workflows for non-expert users of the Southern California Earthquake Center Community Modeling Environment

Workflow systems often present the user with rich interfaces that express all the capabilities and complexities of the application programs and the computing environments that they support. However, non-expert users are better served with simple interfaces that abstract away system complexities and still enable them to construct and execute complex workflows. To explore this idea, we have created a set of tools and interfaces that simplify the construction of workflows. Implemented as part of the Community Modeling Environment developed by the Southern California Earthquake Center, these tools, are integrated into a comprehensive workflow system that supports both domain experts as well as non expert users.

Principles for interactive acquisition and validation of workflows

Workflows, also known as process models, are essential in many science and engineering fields. Workflows express compositions of individual steps or tasks that assembled together account for various aspects of an overall process. When workflows include dozens of components and many links among them, the creation of valid workflows becomes challenging since users have to track many interdependencies and constraints. This article describes principles for assisting users to create valid workflows that are based on two knowledge acquisition systems that we have developed. A shared goal in these projects was to enable end users who do not have computer science backgrounds, such as biologists, military officers or engineers, to create valid end-to-end process models or workflows. Our approach exploits knowledge-rich descriptions of the individual components and their constraints in order to validate the composition, and uses artificial intelligence planning techniques in order to systematically verify formal properties of valid workflows. Both systems analyse partial workflows created by the user, determine whether they are consistent with the background knowledge that the system has, notifies the user of issues to be resolved in the current workflow, and suggests to the user what actions could be taken to correct those issues.

Games, Social Simulations, and Data-Integration for Policy Decisions: The SUDAN Game

In this article, the authors discuss the development of the SUDAN GAME, an interactive model of the country in the time period leading up to the Sudanese referendum on the secession of the South. While many simulations are designed to educate about their subjects, the SUDAN GAME is intended to be a prototype for policy making via gameplay. It is implemented within COSMOPOLIS, a massively multiplayer online game that is currently undergoing development. In this article, the authors discuss the game’s design and how it can be used for policy development, with a focus on the underlying model and some discussion of the COSMOPOLIS implementation. They situate the game relative to other games that have crowdsourced serious problems and discuss the meaning of the policy solutions and collaboration witnessed along players. They conclude with a discussion of future development to be done to improve and expand upon the concepts used in their game.

Testing Behavioral Models with an Online Game

The WarPipe massively multiplayer online game engine promises to enhance games and more serious applications.

Exploring and assessing complex systems' behavior through model-driven storytelling

Complex systems are difficult to analyze because of unknown interactions and dependencies among system components, and between the system and the environment. These interactions and dependencies tend to produce unpredictable behaviors that can often lead to detrimental outcomes. Traditional systems engineering that relies on reductive approaches are not suitable for the analysis and design of complex systems. This recognition has led to the development of new paradigms, methods, and tools that better enable: exploration of a complex systems behavior and tradespace; detection, diagnosis, and visualization of component/subsystem dependencies and interactions; and identification, alerting, and circumvention of potentially undesirable interactions. This paper presents a system model-driven interactive storytelling approach for analyzing interactions and dependencies within complex systems, and between complex systems and the environment. An exemplar complex system is used to convey key elements of the approach. The methodology is applicable for a variety of complex systems such as global supply chains, power and energy management, transportation networks, aerospace and aviation enterprises, and defense systems.

Modeling of Emotional Effects on Decision-making by Game Agents☆

Abstract Game AI agents today do not reflect the affective aspects of human behavior. In particular, game agents do not reflect the effects of human emotional state on an agents decision-making behavior. In rare instances when emotional aspects are addressed in game agent architectures, such behavior tends to be ad hoc and not informed by an underlying theory of emotion, nor validated using actual data. This paper presents a new emotional game agent architecture that is based on an underlying theory of emotion and validated by limited experiments. This architecture manifests a range of emotional effects on game agent behaviors. The overall approach is informed by both appraisal and dimensional theories of emotion. The combination of these theories as underpinnings ensures that emotionally appraised concepts in memory are reflected in the emotional state of the agent, and that such correspondence produces realistic emotional effects on the agents decision-making behavior. The approach is validated through a series of increasingly more sophisticated experiments, in terms of scenario complexity and methods employed. The results are correlated with human data from previous cognitive science experiments. The results show that “lightweight” intelligent agents based on the new game agent architecture can exhibit realistic emotional behavior in real-time decision-making situations encountered in games across various domains.

A Complex Sociotechnical Systems Approach to Provisioning Educational Policies for Future Workforce

Abstract Reforming the U.S. educational system and workforce is a national challenge. Both industry leaders 30 and academics 2,28 concur that improving the quality, quantity [and alignment] of U.S STEM graduates are national imperatives. Models of the U.S. educational system, using complex sociotechnical systems’ approaches and tools that instill systems thinking, offer a holistic perspective to the educational and workforce challenges we face as a nation and allow us to identify and understand challenges associated with workforce preparedness, and increasing the number and technical excellence of STEM graduates 9,13,29 . These models represent a sociotechnical system of systems with various sub-systems, each one representing an inherently complex and interdisciplinary problem of maintaining bi-directional, non-linear feedback relationships between one another. Each system involves multiple disparate stakeholders that need to collaborate within a time-and resource-intensive process while embedded in a larger sociotechnical system, aligned with the people, ideas, and support required to support desired global outcomes, of the system of systems, society and industry in particular 11 .