Author: Karen Myers

We describe a domain-independent framework for plan summarization and comparison that can help a human understand both key strategic elements of an individual plan and important differences among plans.

The challenge we address is to reason about projected resource usage within a hierarchical task execution framework in order to improve agent effectiveness. Specifically, we seek to define and maintain maximally informative guaranteed bounds on projected resource requirements, in order to enable an agent to take full advantage of available resources while avoiding problems of…

We present a BDI-based framework for a cognitive agent that acts as an assistant to a human user by performing tasks on her behalf. This framework accommodates: (1) user delegation of tasks to the agent, which may be inconsistent or infeasible or both, and (2) user-specified guidance and preferences on the execution and management of…

We outline the challenges and opportunities presented by constraint solving in the presence of change and uncertainty, embodied in CALO’s personalized time management and task reasoning and execution systems.

In this paper, we report on a process language, PPL, that we have designed to serve as a bridge between a representation designed for execution and a representation designed for applications such as question answering and explanation generation.

We describe the SRI Procedural Agent Realization Kit (SPARK), a new BDI agent framework that combines scaleability and the clean semantic underpinning of more formal agent frameworks.

We describe the application of plan recognition techniques to support human intelligence analysts in processing national security alert sets by automatically identifying the hostile intent behind them. Identifying the intent enables us to both prioritize and explain the alert sets for succinct user presentation.

We define a qualitative framework for reasoning about plan structure, defining a set of plan relations that characterize key interactions among plan components and a calculus for reasoning qualitatively about the effects of changes.

In this paper, we discuss a number of both formal and practical requirements that must be met to satisfy the demands of large-scale applications. We also briefly describe work on a new BDI agent framework that aims to bridge the gap between formal and practical agent frameworks.

We present a formal framework for robust plan sketching that defines key concepts and algorithms for interpreting and repairing plan sketches for two classes of problems.

We present the novel application of a general-purpose knowledge-based system, SHAKEN, to the specific task of acquiring knowledge for military Course of Action (COA) analysis.

The successful integration and acceptance of many multi-agent systems into daily lives crucially depends on the ability to develop effective policies for adjustable autonomy.