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 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 the components selected and their connections; 2) specifying the workflow flexibly, e.g., topdown, 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

Wings for pegasus: A semantic approach to creating very large scientific workflows

Scientific workflows are being developed for many domains as a paradigm to manage complex scientific computations. In our work, we are challenged with efficiently generating and validating workflows that contain large amounts (hundreds to thousands) of individual computations to be executed over distributed environments. We describe a new approach to workflow creation and validation that uses semantic representations to describe complex scientific applications in a data-independent manner, then automatically generates workflows of computations for given data sets, and finally maps them to available computing resources. We have implemented this approach in Wings and used it to create workflows of thousands of computations, which are submitted to the Pegasus mapping system for execution over grid computing environments

Designing a Massively Multiplayer Online Game / Research Testbed Featuring AI-Driven NPC Communities

Massively Multiplayer Online Games (MMOGs), in their aspect as online communities, represent an exciting opportunity for studying social and behavioral models.  For that purpose we have developed Cosmopolis, a free MMOG containing several key research-oriented features.  First, Cosmopolis consists of an outer game for larger-scale social modeling, as well as a set of subgames suitable for tightly-controlled sandbox-style experiments, all allowing a high level of data logging configuration and control by researchers.  Also, Cosmopolis’s world model incorporates configurable, AI-driven non-player character communities, as a means of researching interactions between individuals and societie