Michael Wolverton

ICAPS Conference 2003 Conference Paper

A Mixed-initiative Framework for Robust Plan Sketching

• Karen L. Myers
• Peter Jarvis
• Mabry Tyson
• Michael Wolverton

Sketching provides a natural and compact means for a user to outline a plan for a high-level objective. Previous work on plan sketching required that sketches be valid, meaning that there be at least one legal completion of the sketch relative to predefined planning knowledge. This paper addresses the problem of plan sketch interpretation when the validity assumption does not hold. We present a formal framework for robust plan sketching that defines key concepts and algorithms for interpreting and repairing plan sketches with respect to two classes of problem: violated applicability conditions and extraneous actions. We also describe a mixed-initiative implementation of this framework that supports a user and the system working collaboratively to refine a plan sketch to a satisfactory solution.

AAAI Conference 1998 Conference Paper

Controlling Communication in Distributed Planning Using Irrelevance Reasoning

• Michael Wolverton

ICAPS Conference 1996 Conference Paper

Segmenting Reactions to Improve the Behavior of a Planning/Reacting Agent

• Michael Wolverton
• Richard Washington

An agent operating in a real-world environment will inevitably encounter some events that demand very quick response---the deadline for an action is short, and the consequences of not acting are high. For these types of events, the agent has a better chance of acting appropriately if it has a pre-stored set of reactions that can be quickly retrieved based on features of the situation. In this paper, we examine the problem of selecting the best set of reactions for an agent to store. In particular, we examine the benefit of including *intervals* of reactions---i. e., executing some reactions only across segments of the complete numeric ranges over which they are defined. We present a decision-theoretic algorithm for selecting the optimal set of reaction intervals, and we present experiments with a computer implementation of that algorithm, called KNEEJERK. The experiments show that the benefit of breaking down reactions into intervals is quite high under a wide range of circumstances.

AAAI Conference 1994 Conference Paper

Retrieving Semantically Distant Analogies with Knowledge-Directed Spreading Activation

• Michael Wolverton

Techniques that traditionally have been useful for retrieving same-domain analogies from small single-use knowledge bases, such as spreading activation and indexing on selected features, are inadequate for retrieving cross-domain analogies from large multi-use knowledge bases. In this paper, we describe Knowledge- Directed Spreading Activation (KDSA), a new method for retrieving analogies in a large semantic network. KDSA uses task-specific knowledge to guide a spreading activation search to a case or concept in memory that meets a desired similarity condition. Specifically, KDSA exploits evaluations of near-analogies encountered during the search to direct the search toward progressively more promising analogies. We describe a specific instantiation of this method for the task of innovative design, and we summarize the theoretical and experimental results used to validate KDSA.