Our group's work in medical decision making has led us to formulate a framework for expert system design, in particular about how the domain knowledge may be decomposed into substructures. We propose that there exist different problem-solving types, i.e., uses of knowledge, and corresponding to each is a separate substructure specializing in that type of problem-solving. Each substructure is in turn further decomposed into a hierarchy of specialist which differ from each other not in the type of problem-solving, but in the conceptual content of their knowledge; e.g.; one of them may specialize in "heart disease," while another may do so in "liver," though both of them are doing the same type of problem solving. Thus ultimately all the knowledge in the system is distributed among problem-solvers which know how to use that knowledge. This is in contrast to the currently dominant expert system paradigm which proposes a common knowledge base accessed by knowledge-free problem-solvers of various kinds. In our framework there is no distinction between knowledge bases and problem-solvers: each knowledge source is a problem-solver. We have so far had occasion to deal with three generic problem-solving types in expert clinical reasoning: diagnosis (classification), data retrieval and organization, and reasoning about consequences of actions. In novice, these expert structures are often incomplete, and other knowledge structures and learning processes are needed to construct and complete them.

One of the challenges increasingly facing intelligence analysts, along with professionals in many other fields, is the vast amount of data which needs to be reviewed and converted into meaningful information, and ultimately into rational, wise decisions by policy makers. The advent of the world wide web (WWW) has magnified this challenge. A key hypothesis which has guided us is that threats come from ideas (or ideology), and ideas are almost always put into writing before the threats materialize. While in the past the'writing' might have taken the form of pamphlets or books, today's medium of choice is themore » WWW, precisely because it is a decentralized, flexible, and low-cost method of reaching a wide audience. However, a factor which complicates matters for the analyst is that material published on the WWW may be in any of a large number of languages. In'Identification of Threats Using Linguistics-Based Knowledge Extraction', we have sought to use Latent Semantic Analysis (LSA) and other similar text analysis techniques to map documents from the WWW, in whatever language they were originally written, to a common language-independent vector-based representation.

"We describe the concept of distributed problem solving and define it as the cooperative solution of problems by a decentralized and loosely coupled collection of problem solvers. This approach to problem solving offers the promise of increased performance and provides a useful medium for exploring and developing new problem-solving techniques. We present a framework called the contract net that specifies communication and control in a distributed problem solver. Task distribution is viewed as an interactive process, a discussion carried on between a node with a task to be executed and a group of nodes that may be able to execute the task. We describe the kinds of information that must be passed between nodes during the discussion in order to obtain effective problem-solving behavior. This discussion is the origin of the negotiation metaphor: Task distribution is viewed as a form of contract negotiation. We emphasize that protocols for distributed problem solving should help determine the content of the information transmitted, rather than simply provide a means of sending bits from one node to another. The use of the contract net framework is demonstrated in the solution of a simulated problem in area surveillance, of the sort encountered in ship or air traffic control. We discuss the mode of operation of a distributed sensing system, a network of nodes extending throughout a relatively large geographic area, whose primary aim is the formation of a dynamic map of traffic in the area. From the results of this preliminary study we abstract features of the framework applicable to problem solving in general, examining in particular transfer of control. Comparisons with PLANNER, CONNIVER, HEARSAY-II, AND PUP6 are used to demonstrate that negotiation—the two-way transfer of information—is a natural extension to the transfer of control mechanisms used in earlier problem-solving systems." Artificial Intelligence 20:63-109.

This study presents a process model of very long-term episodic memory. The process presented is a reconstructive process. The first is used to direct search to appropriate conceptual categories in memory. The other two are used to direct search within the chosen conceptual category. A fourth type of strategy, called executive search strategies, guide search for concepts related to the one targeted for retrieval.

Almost all game tree search procedures used in artificial intelligence are variants on minimaxing. Until recently, it was almost universally believed that searching deeper on the game tree with such procedures would in general yield a better decision. However, recent investigations have revealed the existence of many game trees and evaluation functions which are ‘pathological’ in the sense that searching deeper consistently degrades the decision. This paper extends these investigations in two ways. First, it is shown that whenever the evaluation function satisfies certain properties, pathology will occur on any game tree of high enough constant branching factor.

An extention of the alpha-beta tree pruning strategy to game trees with ‘probability’ nodes, whose values are defined as the (possibly weighted) average of their successors' values, is developed. These ‘*-minimax’ trees pertain to games involving chance but no concealed information. Based upon our search strategy, we formulate and then analyze several algorithms for *-minimax trees. An initial left-to-right depth-first algorithm is developed and shown to reduce the complexity of an exhaustive search strategy by 25–30 percent. An improved algorithm is then formulated to ‘probe’ beneath the chance nodes of ‘regular’ *-minimax trees, where players alternate in making moves with chance events interspersed.

In response to a world in which cancer is a growing global health challenge, there is now a greater need for US Medical Physicists and other Radiation Oncology professionals across institutions to work together and be more globally engaged in the fight against cancer. There are currently many opportunities for Medical Physicists to contribute to alleviating this pressing need, especially in helping enhance access to Medical Physics Education/training and Research Excellence across international boundaries, particularly for low and middle-income countries (LMIC), which suffer from a drastic shortage of accessible knowledge and quality training programs in radiotherapy. Many Medical Physicists aremore » not aware of the range of opportunities that even with small effort could have a high impact. Faculty at the two CAMPEP-accredited Medical Physics Programs in New England: the University of Massachusetts Lowell and Harvard Medical School have developed a growing alliance to increase Access to Medical Physics Education/training and Research Excellence (AMPERE), and facilitate greater active involvement of U.S. Medical Physicists in helping the global fight against cancer and cancer disparities. In this symposium, AMPERE Alliance members and partners from Europe and Africa will present and discuss the growing global cancer challenge, the dearth of knowledge, research, and other barriers to providing life-saving radiotherapy in LMIC, mechanisms for meeting these challenges, the different opportunities for participation by Medical Physicists, including students and residents, and how participation can be facilitated to increase AMPERE for global health.

This book describes a theory of memory representation, organization, and processing for understanding complex narrative texts. The theory is implemented as a computer program called BORIS which reads and answers questions about divorce, legal disputes, personal favors, and the like. The system is unique in attempting to understand stories involving emotions and in being able to deduce adages and morals, in addition to answering fact and event based questions about the narratives it has read. BORIS also manages the interaction of many different knowledge sources such as goals, plans, scripts, physical objects, settings, interpersonal relationships, social roles, emotional reactions, and empathetic responses. The book makes several original technical contributions as well.

In this paper we examine various constraints on the actions of agents in such situations and discuss the effects of these constraints on their derived utility. In particular, we define and analyze basic raiionaliiy; we consider various assumptions about independence; and we demonstrate the advantages of extending the definition of rationality from individual actions to decision procedures.

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.