We summarize the Among the workshop's principal The in using these systems, and (6) computer represent the same knowledge differently workshop on cooperation among environments that facilitate to optimize their particular use heterogeneous intelligent agents, cooperation among human problem of it, or agents could obtain knowledge held July 15 during the 1991 National solvers of diverse abilities. DAI system can use as agents a collection and Edmund Durfee. It was designed Fifty submissions were received, and of existing knowledge-based to bring together researchers and 43 contributors were invited to the systems that have been developed practitioners who are studying how workshop. The workshop had four under a variety of implementation to enable a heterogeneous collection sessions that covered the topics of philosophies. In particular, representations create a special type of agent that is Fifth, agents negotiate and converge must be agreed on able to act as a broker to each of the on decisions by making deals (either before invocation or as a existing agents that need to participate under various types of pressure. Methods must also in a blackboard architecture, so it can be created for agents to assimilate cooperate with other agents.

The Association for the Advancement of Artificial Intelligence held its 1991 Fall Symposium Series on November 15-17 at the Asilomar Conference Center, Pacific Grove, California. This article contains summaries of the four symposia: Discourse Structure in Natural Language Understanding and Generation, Knowledge and Action at Social and Organizational Levels, Principles of Hybrid Reasoning, Sensory Aspects of Robotic Intelligence.

. It is argued that Situated Agents should be designed using a unitaryon-line computational model. The Constraint Net model of Zhang and Mackworth satisfiesthat requirement. Two systems for situated perception built in our laboratory are describedto illustrate the new approach: one for visual monitoring of a robot’s arm, the other forreal-time visual control of multiple robots competing and cooperating in a dynamic world.First proposal for robot soccer.Proc. VI-92, 1992. later published in a book Computer Vision: System, Theory, and Applications, pages 1-13, World Scientific Press, Singapore, 1993.

This article argues that autonomy, not problem-solving prowess, is the key property that defines the intuitive notion of "intelligent creature." The presence of these attributes gives autonomous systems the appearance of nondeterminism, but they can all be present in deterministic artifacts and living systems. We argue that autonomy means having the right kinds of goals and the ability to select goals from an existing set, not necessarily creating new goals. We analyze the concept of goals in problem-solving systems in general and establish criteria for the types of goals that characterize autonomy.

This article argues that autonomy, not problem-solving prowess, is the key property that defines the intuitive notion of "intelligent creature." To build an intelligent artificial entity that will act autonomously, we must first understand the attributes of a system that lead us to call it autonomous. The presence of these attributes gives autonomous systems the appearance of nondeterminism, but they can all be present in deterministic artifacts and living systems. We argue that autonomy means having the right kinds of goals and the ability to select goals from an existing set, not necessarily creating new goals. We analyze the concept of goals in problem-solving systems in general and establish criteria for the types of goals that characterize autonomy.

Each is supported and work to find a general solution to that by a formalized theory of the moves in the class of problems.

Fields 3-8 of table 1 of the survey and general results, a discussion represent purposes, specifically, to define of the four hypotheses, and two sections models (field 3), prove theorems about the at the end of the article that contain details of models (field 4), present algorithms (field 5), the survey and statistical analyses. The next analyze algorithms (field 6), present systems section (The Survey) briefly describes the 16 or architectures (field 7), and analyze them substantive questions I asked about each (field 8). These purposes are not mutually paper. One of the closing sections (An Explanation exclusive; for example, many papers that of the Fields in Table 1) discusses the present models also prove theorems about criteria for answering the survey questions the models.

Embedded agents are computer systems that sense and act on their environments, monitoring complex dynamic conditions and affecting the environment in goal-directed ways. This paper briefly reviews the situated automata approach to agent design and explores issues of planning and action in the situated-automata framework.

"We describe a robot control architecture which combines a stimulus-response subsystem for rapid reaction, with a search-based planner for handling unanticipated situations. The robot agent continually chooses which action it is to perform, using the stimulusresponse subsystem when possible, and falling back on the planning subsystem when necessary. Whenever it is forced to plan, it applies an explanation-based learning mechanism to formulate a new stimulus-response rule to cover this new situation and others similar to it. With experience, the agent becomes increasingly reactive as its learning component acquires new stimulus-response rules that eliminate the need for planning in similar subsequent situations. This Theo-Agent architecture is described, and results are presented demonstrating its ability to reduce routine reaction time for a simple mobile robot from minutes to under a second."In AAAI-90, Vol. 2, pp. 1051– 1058

Universal plans address the tension between reasoned behavior and timely response by caching reactions for classes of possible situations. This technique reduces the average time required to select a response at the expense of the space required to store the cache-the classic time-space trade-off. In his article, Matthew Ginsberg argues from the time extreme and against the space extreme. Although I find both extremes undesirable, I defend an increase in space consumption.