Most human-computer interfaces can be classified according to two dominant metaphors: (1) agent and (2) environment. In the environment metaphor, a model of the task domain is presented for the user to interact with directly. 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.

The Association for the Advancement of Artificial Intelligence held its 1997 Fall Symposia Series on 7 to 9 November in Cambridge, Massachusetts. This article contains summaries of the six symposia that were conducted: (1) Communicative Action in Humans and Machines, (2) Context in Knowledge Representation and Natural Language, (3) Intelligent Tutoring System Authoring Tools, (4) Model-Directed Autonomous Systems, (5) Reasoning with Diagrammatic Representations II, and (6) Socially Intelligent Agents.

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. 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.

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. Currently, the great majority of agent-based systems consist of a single agent. 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.

Research on constraints and agents is emerging at the intersection of the communities studying constraint computation and software agents. Constraint- based reasoning systems can be enhanced by using agents with multiple problem-solving approaches or diverse problem representations. The constraint computation paradigm can be used to model agent consultation, cooperation, and competition. An interesting theme in agent interaction, which is studied here in constraint-based terms, is confronting ignorance: the agent's own ignorance or its ignorance of other agents.

We applied mobile computing to community support and explored mobile computing with a large number of terminals. This article reports on the Second International Conference on Multiagent Systems (ICMAS'96) Mobile Assistant Project that was conducted at an actual international conference for multiagent systems using 100 personal digital assistants (PDAs) and cellular telephones. We supported three types of service: (1) communication services such as e-mail and net news; (2) information services such as conference, personal, and tourist information; and (3) community support services such as forum and meeting arrangements. Participants showed a deep interest in mobile computing for community support.

The Association for the Advancement of Artificial Intelligence held its 1997 Fall Symposia Series on 7 to 9 November in Cambridge, Massachusetts. This article contains summaries of the six symposia that were conducted: (1) Communicative Action in Humans and Machines, (2) Context in Knowledge Representation and Natural Language, (3) Intelligent Tutoring System Authoring Tools, (4) Model-Directed Autonomous Systems, (5) Reasoning with Diagrammatic Representations II, and (6) Socially Intelligent Agents.

Research on constraints and agents is emerging at the intersection of the communities studying constraint computation and software agents. Constraint- based reasoning systems can be enhanced by using agents with multiple problem-solving approaches or diverse problem representations. The constraint computation paradigm can be used to model agent consultation, cooperation, and competition. An interesting theme in agent interaction, which is studied here in constraint-based terms, is confronting ignorance: the agent's own ignorance or its ignorance of other agents.

This confusion is intensified by the "overhyping" of the term agent.

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.