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Editorial: Behavior and Mind as a Complex Adaptive System

Recent advances in cognitive science (Beer, 1995; Brooks, 1991; Chiel and Beer, 1997; Clark, 1997; Hanczyc, Toyota, Ikegami, Packard, & Sugawara, 2007; Ikegami, 2007; Nolfi, 2005; Nolfi & Floreano, 2000; Pfeifer & Scheier, 1999; Tani, 1996; Varela, Thompson, & Rosch, 1991) have clarified that intelligence resides in the circular relationship between the brain of an individual organism, its body, and the environment. More precisely, behavior is (i) a phenomenon resulting from fast nonlinear interactions between the brain of an organism, its body, and the environment (Chiel & Beer, 1997), and (ii) a multiple-scaled phenomenon with different levels of organization in which properties at different levels extend at different timescales and both affect and are affected by lowerand higherlevel properties (Keijzer, 2001; Nolfi, 2005; Paine & Tani, 2005). This implies that behavior is an emergent property; that is, a property that cannot be inferred by an external observer, even on the basis of a complete description of the elements involved in the interactions and of the rules governing the interaction. The emergent nature of behavior has fundamental implications for the practical engineering of artificial behavioral systems. Classical approaches based on explicit design are, in fact, hopeless, because they require the identification of elements and interaction rules (at a micro level) that will lead to the desired behavior (at a macro level) as a result of the interaction occurring at different levels of organization and at different timescales; they involve not only the elementary elements (i.e., the brain of an individual, its body, and the environment) but also the behavioral properties emerging from the interactions. A promising alternative approach consists of self-organizing methods based on evolutionary and/or learning algorithms in which (i) the rules that regulate the interactions at the micro level are encoded into free parameters, which are varied during the adaptive process, and (ii) variations of the free parameters are retained or discarded on the basis of their effect at the macro (behavioral) level (Nolfi, 2005; Paine & Tani, 2005). In fact, these approaches allow us to discover and capitalize on properties emerging from the interactions, without having to identify the relationship between these properties and the interactions that give rise to them. In general terms, this means that behavioral systems are intrinsically adaptive systems. This special issue provides important theoretical and methodological contributions in the study of how behavioral and cognitive skills (including behavioral arbitration, anticipation, mental simulations, and motor planning) can be conceptualized as a complex adaptive system. Moreover, it provides important methodological and experimental contributions for studying how embodied and situated agents can develop these skills autonomously while they interact with the environment.