Roy M. Turner

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Humans and other animals are exquisitely attuned to their context. Context affects almost ail aspects of behavior, and it does so for the most part automatically, without a conscious reasoning effort. This would be a very useful property for an artificial agent to have: upon recognizing its context, the agent's behavior would automatically adjust to fit it.(More)
Medical diagnosis can be considered a planning task: actions are decided on, then executed. However, unlike traditional planning tasks, new information can arise any time, changing the situation and invalidating the plan. In order to cope with this, the reasoner must be able to interleave planning with plan execution. Our approach to this problem is called(More)
To operate successfully in a complex world, intelligent agents must exhibit context-sensitive behavior. Context impacts the appropriateness of virtually all aspects of an agent's behavior, yet most existing reasoning approaches pay little if any attention to explicitly recognizing, reasoning about, and making use of knowledge about the current context. We(More)
Intelligent mission-level control of autonomous underwater vehicles demands an adap-tive reasoner: a program that can create plans for accomplishing mission goals, but that does not overcommit to future details, that remains ready to interrupt what it is doing as the situation evolves, and whose behavior is always appropriate for the context in which the(More)
This paper presents a technique for using a priori contextual knowledge for performing situation assessment for autonomous underwater vehicles (AUVs). What sets this technique apart from other assessment techniques is that it uses explicitly represented contextual schemas to describe discrete contexts that may occur in the world. A modified version of the(More)