Second, These sections describe how Phoenix agents there are motivating issues, of plan in real time but do not provide the which the foremost is to understand minute detail that is offered elsewhere (Cohen how complex environments et al. forthcoming). The next section illustrates constrain on the design of Phoenix agents controlling a forest fire. We seek general The last section describes the current status of rules that justify and explain the project and our immediate goals. The terms in these rules describe The Phoenix task is to control simulated characteristics of environments, forest fires by deploying simulated bulldozers, tasks and behaviors, and the crews, airplanes, and other objects. We discuss architectures of agents. Phoenix Environment, Layers 1 and 2 but Phoenix is a commentary on the Phoenix Simulator. In the following pages, we describe Phoenix from the perspective of our technical aims and motives. The second section describes the Phoenix task--controlling simulated forest fires-- and explains why we use a simulated environment instead of a real, physical one. The two lowest layers of Phoenix, described in The Phoenix Environment, Layers 1 and 2, implement the simulated environment and maintain the illusion that the forest fire and agents are acting simultaneously. Above these layers are two others: a Figure 2. Fire at 12:30 Bulldozers are Close to organization of multiple Meeting at the Fire Front. The left pane displays the real world; the right pane displays fireboss sees it. Firefighting objects are also and other agents are semiautonomous.

Artificial Intelligence, as a maturing scientific/engineering discipline, is beginning to find its niche among the variety of subjects that are relevant to intelligent, perceptive behavior. A view of AI is presented that is based on a declarative representation of knowledge with semantic attachments to problem-specific procedures and data structures. Several important challenges to this view are briefly discussed. It is argued that research in the field would be stimulated by a project to develop a computer individual that would have a continuing existence in time.

Our own early attempts (as devoted users of LISP) to use PROLOG convinced us that it would be worth the effort to create within LISP a faithful implementation of Kowalski's logic programming idea. We felt it would be very convenient to be able to set up a knowledge base of assertions inside a LISP workspace, and to compute the answers to queries simply by executing appropriate function calls.In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.