Author: Karen Myers

We describe a plan-authoring system called PASSAT (Plan Authoring System based on Sketches, Advice, and Templates) that combines interactive tools for constructing plans with a suite of automated and mixed-initiative capabilities designed to complement human planning skills.

This paper considers the problem of conflicting guidance for agents, making contributions in two areas: outlining a space of conflict types, and defining resolution methods that provide robust agent operation in the face of conflicts.

This paper considers the problem of conflicting guidance for agents, making contributions in two areas: (a) outlining a space of conflict types, and (b) defining resolution methods that provide robust agent operation in the face of conflicts.

This paper presents a framework called CODA that provides targeted information dissemination among distributed human planners as a way of improving coordination.

We have developed an initial framework that models decision making, reasoning about constraints, and learning at multiple levels of abstraction and multiple time scales, within and across agents.

We describe an incremental and adaptive approach to integrating hierarchical task network planning and constraint-based scheduling.

This paper presents a framework for directability of a community of agents by a human supervisor that focuses on three dimensions: adjustable agent autonomy, strategy preference, and community-level constraints.

The CODA system provides targeted information dissemination among distributed human planners as a way of improving coordination.

This paper presents a framework for the directability of agents, in which a human supervisor can define policies to influence agent activities at execution time.

This paper introduces two contrasting methods for planning with conflicting advice, suited to different user requirements. Soft enforcement embodies a heuristic approach that prefers planning choices that are consistent with specified ad-vice but will disregard advice that introduces conflicts.

This paper describes how techniques from the AI community, specifically reactive control, planning, and scheduling, could be leveraged to develop powerful, next-generation adaptive workflow engines that provide many of the these advanced process management capabilities.

This article reports on the first phase of the continuous planning and execution framework (CPEF), a system that employs sophisticated plan-generation, -execution, -monitoring, and -repair capabilities to solve complex tasks in unpredictable and dynamic environments.