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Springer Handbook of Robotics pp 891–909Cite as

Behavior-Based Systems

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Abstract

Nature is filled with examples of autonomous creatures capable of dealing with the diversity, unpredictability, and rapidly changing conditions of the real world. Such creatures must make decisions and take actions based on incomplete perception, time constraints, limited knowledge about the world, cognition, reasoning and physical capabilities, in uncontrolled conditions and with very limited cues about the intent of others. Consequently, one way of evaluating intelligence is based on the creatureʼs ability to make the most of what it has available to handle the complexities of the real world. The main objective of this chapter is to clarify behavior-based systems and their use in single- and multi-robot autonomous control problems and applications. The chapter is organized as follows. Section 38.1 overviews robot control, introducing behavior-based systems in relation to other established approaches to robot control. Section 38.2 follows by outlining the basic principles of behavior-based systems that make them distinct from other types of robot control architectures. The concept of basis behaviors, the means of modularizing behavior-based systems, is presented in Sect. 38.3. Section 38.4 describes how behaviors are used as building blocks for creating representations for use by behavior-based systems, enabling the robot to reason about the world and about itself in that world. Section 38.5 presents several different classes of learning methods for behavior-based systems, validated on single-robot and multi-robot systems. Section 38.6 provides an overview of various robotics problems and application domains that have successfully been addressed with behavior-based control. Finally, Sect. 38.7 concludes the chapter.

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Abbreviations

AAAI:

American Association for Artificial Intelligence

AuRA:

autonomous robot architecture

BLE:

broadcast of local eligibility

HRI:

human–robot interaction

RL:

reinforcement learning

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Authors and Affiliations

  1. Computer Science Department, University of Southern California, 3650 McClintock Avenue, 90089, Los Angeles, CA, USA

    Maja J. Matarić Prof

  2. Department of Electrical Engineering and Computer Engineering, Université de Sherbrooke, 2500 Boulevard Université, J1K 2R1, Sherbrooke, Québec, Canada

    François Michaud

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  1. Maja J. Matarić Prof
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  2. François Michaud
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  1. PRISMA Lab, Dipartimento di Informatica e Sistemistica, Universitá degli Studi di Napoli Federico II, 80125, Napoli, Italy, Via Claudio 21

    Bruno Siciliano Prof.

  2. Artificial Intelligence Laboratory, Department of Computer Science, Stanford University, 94305-9010, Stanford, CA, USA

    Oussama Khatib Prof.

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Matarić, M.J., Michaud, F. (2008). Behavior-Based Systems. In: Siciliano, B., Khatib, O. (eds) Springer Handbook of Robotics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30301-5_39

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