Rationale-Supported Mixed-Initiative Case-Based Planning
نویسندگان
چکیده
Mixed-initiative planning envisions a framework in which automated and human planners interact to jointly construct plans that satisfy specific objectives. In this paper, we report on our work engineering a robust mixed-initiative planning system. Human planners rely strongly on past planning experience to generate new plans. ForMAT is a case-based system that supports human planning through the accumulation of user-built plans, query-driven browsing of past plans, and several plan functionality analysis primitives. Prodigy/Analogy is an automated AI planner that combines generative and case-based planning. Stored plans are annotated with plan rationale and reuse involves adaptation driven by this rationale. Our system, MI-CBP, integrates ForMAT and Prodigy/Analogy into a real-time message-passing mixed-initiative planning system. The main technical approach consists of allowing the user to specify and link objectives that enable the system to capture and reuse plan rationale. We present MI-CBP and its concrete application to the domain of military force deployment planning. This synergistic system increases the planning efficiency of human planners through automated suggestion of similar past plans and plausible plan modifications.
منابع مشابه
Towards Mixed-Initiative Rationale-Supported Planning
This paper introduces our work on mixed-initiative, rationale-supported planning. The work centers on the principled reuse and modi cation of past plans by exploiting their justi cation structure. The goal is to record as much as possible of the rationale underlying each planning decision in a mixed-initiative framework where human and machine planners interact. This rationale is used to determ...
متن کاملSupporting Combined Human and Machine Planning: An Interface for Planning by Analogical Reasoning
Realistic and complex planning situations require a mixed-initiative planning framework in which human and automated planners interact to mutually construct a desired plan. Ideally, this joint cooperation has the potential of achieving better plans than either the human or the machine can create alone. Human planners often take a case-based approach to planning, relying on their past experience...
متن کاملSupporting Combined Human and Machine Planning: The Prodigy 4.0 User Interface Version 2.0*
Realistic and complex planning situations require a mixed-initiative planning framework in which human and automated planners interact to mutually construct a desired plan. Ideally, this joint cooperation has the potential of achieving better plans than either the human or the machine can create alone. Human planners often take a case-based approach to planning, relying on their past experience...
متن کاملMixed-Initiative Case Replay
Mixed-initiative case replay introduces an active human into the case-based planning process. The goals of this novel technique are to utilize the strengths of machine-based case replay to improve human performance and to allow a human to override a machine’s abstract representation of an actual domain. The synthesis of these two approaches in a planning domain enables flexible solutions to pla...
متن کاملRationale in planning: causality, dependencies, and decisions
Traditional approaches to plan representation focused on the generation of a sequence of actions and orderings Knowledge rich models which incorporate plan rationale provide bene ts to the planning process in a number of ways The use of rationale in planning is reviewed in terms of causality dependencies and decisions Each dimension addresses practical issues in the planning process and adds va...
متن کامل