Behavior-Based Artificial Intelligence Pattie Maes MIT Media-Laboratory Presentation by: Derak Berreyesa UNR, CS Department

Abstract Uses behavior-based artificial intelligence as a new approach to studying intelligence. Deals with autonomous systems that must deal with changing goals in an unpredictable environment.

Two approaches to AI Knowledge-Based AI Knowledge based systems have prior knowledge about the environment and there task. Behavior-Based AI React to there changing environment and goals They “behave” in a problem domain.

Knowledge-Based AI Isolated and advanced competences. “Closed” systems that only connect to the user, not the environment. Deal with one problem at a time. Uses static knowledge structures to solve problems. Don’t have to adapt to changing situations. When creating an autonomous system a computer takes over as the user.

Behavior-Based AI Has several competences but they are not as intelligent as isolated competence would be. “Open” system that has little time to react. Decides itself what the problem to be solved next is. Relies more on producing behavior than knowledge. Emphasis on adaptation.

Behavior-Based problem solving A system that can learn has to rely less on planning. Environment can be exploited. Learn over time. Interacts in society to help accomplish tasks.

A Mobile Robot Knowledge-Based would create a model of the office to update as often as possible. It would include the location of the robot itself and the location of certain objects. Behavior-Based would have specific modules for wall following, going through doors, etc.

An Interface Agent Knowledge-Based will learn all it can about what it should prompt the user for and/or try to do when the user does something. Behavior-Based will have a each separate module try to learn about it’s own specialized task.

Conclusion Behavior-Based AI have proven to be very efficient so far. More fundamental research needs to be done. A better understanding of the underlying principles.