Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

A system is autonomous if it uses its own information to modify itself and its environment to enhance its survival, responding to both environmental and internal stimuli to modify its basic functions to increase its viability. Autonomy is the foundation of functionality, intentionality and meaning. Autonomous systems accommodate the unexpected through self-organizing processes, together with some constraints that maintain autonomy. Early versions of autonomy, such as autopoiesis and closure to efficient cause, made autonomous systems dynamically closed to information. This contrasts (...) with recent work on open systems and information dynamics. On our account, autonomy is a matter of degree depending on the relative organization of the system and system environment interactions. A choice between third person openness and first person closure is not required. (shrink)

This article focuses on the problem of representational content. Accounting for representational content is the central issue in contemporary naturalism: it is the major remaining task facing a naturalistic conception of the world. Representational content is also the central barrier to contemporary cognitive science and artificial intelligence: it is not possible to understand representation in animals nor to construct machines with genuine representation given current (lack of) understanding of what representation is. An elaborated critique is offered to current approaches to (...) representation, arguing that the basic underlying approach is, at root, logically incoherent, and, thus, that standard approaches are doomed to failure. An alternative model of representation - interactivism - is presented that avoids or solves the problems facing standard approaches. Interactivism is framed by a version of functionalism, and a naturalization of that functionalism completes an outline of a naturalization of representation and representational content. (shrink)

Abstract Many anticipatory systems cannot in themselves act meaningfully or represent intentionally. This stems largely from the derivative nature of their functionality. All current artificial control systems, and many living systems such as organs and cellular parts of organisms derive any intentionality they might have from their designers or possessors. Derivative functionality requires reference to some external autonomously functional system, and derivative intentionality similarly requires reference to an external autonomous intentional system. The importance of autonomy can be summed up in (...) the following slogan: No meaning without intention; no intention without function; no function without autonomy. This paper develops the role of autonomy to show how learning new tasks is facilitated by autonomy, and further by representational capacities that are functional for autonomy. (shrink)

Function emerges in certain kinds of far-from-equilibrium systems. One important kind of function is that of interactive anticipation, an adaptedness to temporal complexity. Interactive anticipation is the locus of the emergence of normative representational content, and, thus, of representation in general: interactive anticipation is the naturalistic core of the evolution of cognition. Higher forms of such anticipation are involved in the subsequent macro-evolutionary sequence of learning, emotions, and reflexive consciousness.

Wayne D. Christensen and Cliff A. Hooker.

This paper attempts to establish a systems-semiotic framework explaining creativity in the design process, where the design process is considered to have as its basis the cognitive process. The design process is considered as the interaction between two or more cognitive systems resulting in a purposeful and ongoing transformation of their already complex representational structures and the production of newer ones, in order to fulfill an ill-defined goal. Creativity is considered as the result of an emergence of organizational complexity in (...) each cognitive system participating in the design process, while it is trying to purposefully incorporate new constraints in its meaning structures. The meanings generated in each system are identified as the contingent and anticipatory content of its representations, and where self-organization is the dominant process in which they are continuously involved. Furthermore, Peircean semiotic processes appear to provide the functionality needed by the emergent representational structures in order to complete the cycle of a creative design process. Creativity originates in the abductive stage of the semiotic process, the fallible nature of which is maintained in the proposed framework by the fact that the respective emergent representations can be misfits. The nodal points of the framework are identified and analyzed showing that a cognitive system needs the whole interactive anticipatory cycle in order to engage in a creative design process. (shrink)

Both natural and engineered systems are fundamentally dynamical in nature: their defining properties are causal, and their functional capacities are causally grounded. Among dynamical systems, an interesting and important sub-class are those that are autonomous, anticipative and adaptive (AAA). Living systems, intelligent systems, sophisticated robots and social systems belong to this class, and the use of these terms has recently spread rapidly through the scientific literature. Central to understanding these dynamical systems is their complicated organisation and their consequent capacities for (...) re- and self- organisation. But there is at present no general analysis of these capacities or of the requisite organisation involved. We define what distinguishes AAA systems from other kinds of systems by characterising their central properties in a dynamically interpreted information theory. (shrink)

Anticipation allows a system to adapt to conditions that have not yet come to be, either externally to the system or internally. Autonomous systems actively control their own conditions so as to increase their functionality (they self-regulate). Living systems self-regulate in order to increase their own viability. These increasingly stronger conditions, anticipation, autonomy and viability, can give an insight into progressively stronger classes of models of autonomy. I will argue that stronger forms are the relevant ones for Artificial Life. This (...) has consequences for the design of and accurate simulation of living systems. Keywords: autonomy, modelling, function, simulation, anticipation, emergence DUBOIS’ CONJECTURE Autonomy basically means self-regulation. Self-regulation implies internal control of system states to achieve greater functionality, either internally or interactively with the environment. Functionality, as a teleological notion, implies that the system must be directed by likely future states; that is, it must anticipate and (possibly) adapt to likely future states. Functionality does not require autonomy (assuming functional goals are externally set), but merely that current states of the system can select suitable future states on the basis of suitable input. In this.. (shrink)