Author: Karen Myers

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.

In an effort to encourage the exchange of ideas, this paper explores how techniques from intelligent reactive control might be leveraged to provide adaptivity within workflow technologies, while also acknowledging their current limitations for certain workflow requirements.

This paper 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.

This paper addresses both theoretical and practical issues relevant to reasoning about locations. Techniques for the efficient operationalization of the belief revision rules in planning frameworks are presented.

With the objective of fostering increased user participation in the planning process, this paper presents an HTN-based framework for the abductive completion of plan sketches. Within this framework, user-supplied outlines of partial plans (possibly spanning multiple abstraction levels) are interpreted and completed.

Autonomy has many different aspects; here we concentrate on three central ones: the ability to attend to another agent, to take advice about the environment, and to carry out assigned tasks.

Mobile robots, if they are to perform useful tasks and become accepted in open environments, must be autonomous: capable of acquiring information and performing tasks without programmatic intervention.

We briefly describe the history of ARPI projects at SRI International. Such agents require several capabilities for successful operation, such as monitoring the world, responding appropriately to important events, accepting goals, synthesizing plans for achieving those goals, and executing the plans while continuing to be responsive to changes in the world

This paper describes PRSLite, a task-level controller grounded in a procedural knowledge approach to action description.

This paper describes an Advisable Planner framework that marries an advice-taking interface to AI planning technology. The framework is designed to enable users to interact with planning systems at high levels of abstraction in order to influence the plan generation process in terms that are meaningful to them.

The Advisable Planner project seeks to make AI planning technology more accessible and easier to use through the metaphor of advice-taking. In particular, we are developing an advisable planning system that marries an advice-taking interface to state-of-the-art planning technology.

The CYPRESS system is a domain-independent framework for defining persistent agents with this full range of behavior. It has been used for several demanding applications, including military operations, real-time tracking, and fault diagnosis.