Maja J Mataric´

Behavior-Based Control: A Brief Primer

Behavior-based control is one of the three dominant paradigms for robot control. The other two are reactive control and hybrid control.

Behavior-based controllers consist of a collection of behaviors. Behaviors are processes or control laws that achieve and/or maintain goals. For example, 'avoid-obstacles' maintains the goal of preventing collisions, 'go-home' achieves the goal of reaching some home destination. Behaviors can be implemented either in software or hardware; as a processing element or a procedure. Each behavior can take inputs from the robot's sensors (e.g., camera, ultrasound, infra-red, tactile) and/or from other behaviors in the system, and send outputs to the robot's effectors (e.g, wheels, grippers, arm, speech) and/or to other behaviors. Thus, a behavior-based controller is a structured network of such interacting behaviors. Note that behaviors themselves can have state, and can form representations when networked together. Thus, unlike reactive systems, behavior-based systems are not limited in their expressive and learning capabilities.

The key difference between behavior-based and hybrid systems is in the way representation and time-scale are handled. Hybrid systems typically employ a low-level reactive system that functions on a short time-scale, and a high-level planner that functions on a long time-scale. The two interact through a middle layer. Consequently hybrid systems are often implemented with so-called three-layer architectures.

In contrast, behavior-based systems attempt to make the representation, and thus the time-scale, of the system uniform. Behavior-based representations are parallel, distributed, and active, in order to accommodate the real-time demands of other parts of the system. Furthermore, they are implemented using the behavior structure, much like the rest of the system.

There are a great many examples of behavior-based mobile robots. Currently, behavior-based control appears to be the de-facto standard for multi-robot control, due to its scalable properties. For a textbook on behavior-based control, see: Behavior-Based Robotics by R. Arkin

The following are my papers specifically on the topic of behavior-based control:

  • Maja J Mataric´, "Behavior-Based Robotics", in the MIT Encyclopedia of Cognitive Sciences, Robert A. Wilson and Frank C. Keil, eds., MIT Press, April 1999, 74-77.

  • Maja J Mataric´, " Behavior-Based Control: Examples from Navigation, Learning, and Group Behavior", Journal of Experimental and Theoretical Artificial Intelligence, special issue on Software Architectures for Physical Agents, 9(2-3), H. Hexmoor, I. Horswill, and D. Kortenkamp, eds., 1997, 323-336.

  • Maja J Mataric´, "Behavior-Based Systems: Main Properties and Implications" in Proceedings, IEEE International Conference on Robotics and Automation, Workshop on Architectures for Intelligent Control Systems, Nice, France, May 1992, 46-54.

  • Maja J Mataric´, "Behavior-Based Robotics as a Tool for Synthesis of Artificial Behavior and Analysis of Natural Behavior", Trends in Cognitive Science, 2(3), Mar 1998, 82-87.

  • Maja J Mataric´, "Integration of Representation Into Goal-Driven Behavior-Based Robots", in IEEE Transactions on Robotics and Automation, 8(3), Jun 1992, 304-312.

    Our contribution to the field of behavior-based systems has been in the following areas:

  • introducing representation into behavior-based systems
  • introducing the concept of basis behaviors for principled design of behavior-based systems
  • applying behavior-based systems to single-robot and multi-robot control
  • enabling & facilitating adaptation and learning in single-robot and multi-robot systems by using behaviors as the underlying representation
  • using behaviors as the representation corresponding to biological motor primitives in complex motor control
  • using behaviors to model perceptual-motor primitives in learning by imitation

    For details about these efforts, please see my projects page and my publications page.

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