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This paper provides an overview of the bottom-up approach to artificial intelligence (AI), commonly referred to as behavior-oriented AI. The behavior-oriented approach, with its focus on the interaction between autonomous agents and their environments, is introduced by contrasting it with the traditional approach of knowledge-based AI. Different notions of autonomy are discussed, and key problems of generating adaptive and complex behavior are identified. A number of techniques for the generation of behavior are introduced and evaluated regarding their potential for realizing different aspects of autonomy as well as adaptivity and complexity of behavior. It is concluded that, in order to realize truly autonomous and intelligent agents, the behavior-oriented approach will have to focus even more on lifelike qualities in both agents and environments.