Agent-based systems technology has generated lots of excitement in recent years because of its promise as a new paradigm for conceptualizing, designing, and implementing software systems. This promise is particularly attractive for creating software that operates in environments that are distributed and open, such as the internet. Currently, the great majority of agent-based systems consist of a single agent. However, as the technology matures and addresses increasingly complex applications, the need for systems that consist of multiple agents that communicate in a peer-to-peer fashion is becoming apparent. Central to the design and effective operation of such multiagent systems (MASs) are a core set of issues and research questions that have been studied over the years by the distributed AI community. In this article, I present some of the critical notions in MASs and the research work that has addressed them. I organize these notions around the concept of problem-solving coherence, which I believe is one of the most critical overall characteristics that an MAS should exhibit.

Interacting with a computer requires adopting some metaphor to guide our actions and expectations. Most human-computer interfaces can be classified according to two dominant metaphors: (1) agent and (2) environment. Interactions based on an agent metaphor treat the computer as an intermediary that responds to user requests. In the environment metaphor, a model of the task domain is presented for the user to interact with directly. The term agent has come to refer to the automation of aspects of human-computer interaction (HCI), such as anticipating commands or autonomously performing actions. Norman's 1984 model of HCI is introduced as reference to organize and evaluate research in human-agent interaction (HAI). A wide variety of heterogeneous research involving HAI is shown to reflect automation of one of the stages of action or evaluation within Norman's model. Improvements in HAI are expected to result from a more heterogeneous use of methods that target multiple stages simultaneously.

Buzzeo (Phoenix, Ariz.), a software engineering firm, has developed a highly adaptable self-service application that automates various administrative Bell Helicopter Textron (Fort Worth, rapid transit (BART) system. The lab functions for the higher-education Tex.), a manufacturer of helicopters, will develop a system to better train marketplace. This rule-based has implemented an intelligent system both new BART operators and those system has helped Buzzeo cut its to automate the procurement needing periodic retraining. ATS enables customers traffic problems at commercial airports. Technical Library at the to track packages through a The $9.3 million, two-story Phillips site on Kirtland Air Force Base, nationwide 800 number by simply building, called the Surface Development New Mexico, is using advanced pattern-recognition stating a tracking number to learn and Test Facility, is being built at technology to design the status of a package.

In the last few years, we have witnessed a major growth in the use of empirical methods in AI. In part, this growth has arisen from the availability of fast networked computers that allow certain problems of a practical size to be tackled for the first time. There is also a growing realization that results obtained empirically are no less valuable than theoretical results. Experiments can, for example, offer solutions to problems that have defeated a theoretical attack and provide insights that are not possible from a purely theoretical analysis. I identify some of the emerging trends in this area by describing a recent workshop that brought together researchers using empirical methods as far apart as robotics and knowledge-based systems.

Lull's writings advanced the idea vert to Christianity because of a cognitive that non-mathematical reasoning can in artificial intelligence have defect. Some of appreciate the vast array of the combinations process, and that reasoning the most fundamental, surely, are that of God's or Christ's virtues. But does not proceed by syllogism, but by thinking is a computational process, Lull believed that infidels could be combinatorics. The decomposition can be made mechanical, and that the Further, he thought that a representation and recombination of attributes can be mathematics of computation involves of those combinations could represented by the decomposition and combinatorics. All of these ideas have be effectively presented by means of recombination of symbols, and that, as their origin, so far as we know, in the appropriate machines, and that was Lull's devices illustrate, is a process that work of an eccentric 13th century the key to his new method.

The Eleventh International Workshop on Qualitative Reasoning was held in Cortona, Italy, on 3 to 6 June 1997. Participants included scientists from both qualitative reasoning and quantitative mathematical modeling communities. This article summarizes the significant issues and discussion raised during the workshop.

What I like to see is more international volumes with a balanced set of multicultural views from the United States, Europe, and Asia. This goes back to Roy D'Andrade's However, a number of To my mind, some of the chapters to answer the question, "What is cognitive issues are repeated across chapters, and indulge in lots of talk without any science?" The book does answer it is not clear that the authors of each clear detail or data. I found that the question, in so far as it can in such chapter had a chance to read the other Daniel Schacter's chapter on memory a young field, by providing a range of chapters while they wrote theirs. The was too full of references to other chapters tackling cognitive science different parts of the book could have work and had little of his own discussion; from different points of view.

A false negative means that fraud, bad credit, or intrusion passes unnoticed, with potential loss of revenue or security. This workshop focused primarily papers, 10 of which were selected for with the Fourteenth National on what might loosely be termed presentation at the workshop. These Conference on Artificial Intelligence "improper behavior," which includes 10 papers were grouped into 3 categories. However, Glasgow applying classification techniques to were over 50 attendees, with a balanced does discuss the estimation of "inherent fraud and risk problems, including the mix of university and industry risk," which is the bread and butter use of clustering techniques to generate researchers. We sought participants data, highly skewed distributions ("improper Columbia University, and Phillip Chan to discuss and explore common behavior" occurs far less frequently of Florida Institute of Technology).

Humans are social creatures. Much of our intelligence derives from our ability to manipulate our environment through collaborative endeavors. Most extant computer programs and interfaces do little to take advantage of such manifestly human talents and interests, leaving broad avenues of human-computer communication unexplored. Although it is still considered controversial, there are many who believe the harnessing of social communication to be rich in possibilities for modern software. In this article, we look at a number of autonomous agent systems that embody their intelligence at least partially through the projection of a believable, engaging, synthetic persona. Among other topics, we touch briefly on samples of research that explore synthetic personality, representations of emotion, societies of fanciful and playful characters, intelligent and engaging automated tutors, and users projected as avatars into virtual worlds.

Cognitive modeling has traditionally leads to, on the one hand, the apparent he workshop entitled "Computational of Power," which we cochaired been underrepresented in American lack of regularities and, on the and organized, was held at the Thirteenth Association for Artificial Intelligence other hand, superfluous regularities National Conference on Artificial conferences and journals. However, its that can be misleading, which is even Intelligence (AAAI-96) on 5 importance should not be underestimated.