Critiquing: Effective Decision Support in Time-Critical Domains (Dissertation Proposal)

The effective communication of information is an important concern in the design of an expert consultation system. Several researchers have chosen to adopt a critiquing mode, in which the system evaluates and reacts to a solution proposed by the user rather than presenting its own solution. In this proposal, I present an architecture for a critiquing system that functions in real-time, during the process of developing and executing a management plan in time-critical situations. The architecture is able to take account of and reason about multiple, interacting goals and to identify critical errors in the proposed management plan. This architecture is being implemented as part of the TraumAID system for the management of patients with severe injuries

Upholding the Maxim of Relevance during Patient-Centered Activities

This paper addresses "kinds and focuses of relevance" that a language-generating clinical decision-support system should adhere to during activities in which a health care provider's attention is on his or her patient and not on a computer screen. During such "patient-centered" activities, utterances generated by a computer system intrude on patient management. They must be thus seen by HCPs as having immediate clinical relevance, or, like the continual ringing of ICU monitors, they will be ignored. This paper describes how plan recognition and plan evaluation can be used to achieve clinical relevance. The work is being done in the context of the TraumAID project, whose overall goal is to . improve the delivery of quality trauma care during the initial definitive phase of patient management. Given an early pilot study that showed that physicians using TraumAID disliked the continuous presentation of its entire management plan, we decided to explore how TraumAID could restrict commentary to only those situations in which a comment could make a clinically significant difference to patient management. We took advantage of the fact that actions that involve resources that need to be brought to the trauma bay or that can only be done elsewhere must be ordered. Since or- ders can be rescinded, comments pointing out problems with an order can potentially make a clinically significant difference to patient management. The contributions of this paper are (1) pointing out additional *This work has been supported in part by the Army Research Organization under grant DAAL03-89C0031PRI, the National Library of Medicine under grant R01 LM05217-01 and the Agency for Health Care Policy and Research under grant RO1 HS06740. The authors would like to thank Mark Steedman and Jonathan Kay..

Towards an Intelligent Tutor for Mathematical Proofs

Computer-supported learning is an increasingly important form of study since it allows for independent learning and individualized instruction. In this paper, we discuss a novel approach to developing an intelligent tutoring system for teaching textbook-style mathematical proofs. We characterize the particularities of the domain and discuss common ITS design models. Our approach is motivated by phenomena found in a corpus of tutorial dialogs that were collected in a Wizard-of-Oz experiment. We show how an intelligent tutor for textbook-style mathematical proofs can be built on top of an adapted assertion-level proof assistant by reusing representations and proof search strategies originally developed for automated and interactive theorem proving. The resulting prototype was successfully evaluated on a corpus of tutorial dialogs and yields good results.Comment: In Proceedings THedu'11, arXiv:1202.453

Critiquing: Effective Decision Support in Time-Critical Domains

The TraumAID system is a tool for assisting physicians during the initial definitive management phase of patients with severe injuries. Originally, TraumAID was conceived as a rule-based expert system combined with a planner. After this architecture had been implemented and evaluated, we began to face the issue of how TraumAID could communicate its plans to physicians in order to influence their behavior and have a positive effect on patient outcome. It was hypothesized that a critiquing approach, in which the system is told what actions the user intends to carry out and produces a critique in response to those intentions, might be appropriate. To meet the needs of physicians engaged in managing trauma cases, critiques must be updated and made available rapidly. They must be clear and succinct, containing only relevant information while still including enough justification ..

Real-time Critiquing of Integrated Diagnosis/Therapy Plans

In the past, little attention has been paid to critiquing in domains in which reasoning, planning and action are interleaved, or in which actions can change the agent's knowledge in ways that affect subsequent reasoning and planning. This paper discusses the demands these characteristics make on a critiquing system. The goal-directed approach to critiquing that I am developing interacts with a planner both to infer the user's goals and to determine the system's preferences. The model is able to detect interacting goals and comment when two goals may be addressed with a single action. It also detects when unpredictable outcomes may affect actions that have been planned for. The model is being implemented as an interface to TraumAID, a decision support system for the management of severe injuries. 1 Introduction Since its introduction a little more than ten years ago, the term critiquing has been used to describe a wide variety of systems. Basically, a critiquing system is anything that..

A Bias towards Relevance: Recognizing plans where goal minimization fails

Domains such as multiple trauma management, in which there are multiple interacting goals that change over time, are ones in which plan recognition 's standard inductive bias towards a single explanatory goal is inappropriate. In this paper we define and argue for an alternative bias based on identifying contextually "relevant" goals. We support this claim by showing how a complementary planning system in TraumAID 2.0, a decision-support system for the management of multiple trauma, allows us to define a four-level scale of relevance and therefore, of measurable deviations from relevance. This in turn allows definition of a bias towards relevance in the incremental recognition of physician plans by TraumAID 's critiquing interface, TraumaTIQ. Introduction Domains such as multiple trauma management, in which there are multiple interacting goals that change over time, are ones in which plan recognition's standard inductive bias towards a single explanatory goal is inappropriate. Yet som..