ion is one of most important tools of the computer scientist. In fact, the design and implementation of complex systems cannot be done without it. In general, abstraction is used to simplify elements of complex systems such that complexity is lowered without decreasing performance significantly. In artificial intelligence and machine learning, its main goal is to lower the complexity of reasoni...

Recently, in both the neuroscience and adaptive behaviour communities, there has been growing interest in the interplay of multiple timescales within neural systems. In particular, the phenomenon of neuromodulation has received a great deal of interest within neuroscience and a growing amount of attention within adaptive behaviour research. This interest has been driven by hypotheses and eviden...

Complex adaptive systems consist of a multitude of agents from whose individual adaptation efforts the adaptive behavior of the system as a whole emerges. In this paper it will be argued that capitalism is a complex adaptive system. Except for its particular mode of production many of its features are typical for such a system. A case in point is the way in which economic growth emerges as a co...

in this paper, we introduce a new hyperchaotic complex t-system. this system has complex nonlinear behavior which we study its dynamical properties including invariance, equilibria and their stability, lyapunov exponents, bifurcation, chaotic behavior and chaotic attractors as well as necessary conditions for this system to generate chaos. we discuss the synchronization with certain and uncerta...

This paper gives 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 ...

This paper presents a novel multidisciplinary architecture which unites recent research in cognitive science and connectionism to develop an integrated solution, and computational model, for the acquisition and performance of recognitional and metacognitive skills by human subjects and intelligent agents. This work builds on three key components: (a) the Recognition / Metacognition model of hum...

This study explored the adaptive behavior of primary school students with visual impairments, as well as the impact of educational setting on their adaptive behavior. Instrumentation included an informal questionnaire and the Vineland Adaptive Behavior Scales. Participants were 36 primary school students with visual impairments. The educational setting had an effect on Daily Living Skills and S...

Introduction D ECISION MAKING IS A VERY CHALLENGING PROBLEM, both in human thinking as in artificial intelligence systems. While you are reading this text, many things take place inside your brain. For one thing, you are trying to stay focused on reading this, you are trying to keep yourself nourished, you are trying to remember to send this very important e-mail, and so on. Furthermore, you kn...

How do animals use the same peripheral structures to generate different behavioral responses? Three different neuronal architectures have been proposed to mediate this task: dedicated circuitry; distributed circuitry; and reorganizing circuitry. This review will critically examine the evidence for these different architectures in invertebrate circuits, and then examine the evidence for them in ...

This study was conducted to examine an adaptation of the Vineland Adaptive Behavior Scale (VABS) [Sparrow, S. S., Balla, D. A., & Cicchetti, D. V. (1984). The Vineland Adaptive Behavior Scales. Circle Pines, MN: America Guidance Service; Sparrow, S. S., Balla, D. A., & Cicchetti, D. V. (2005). Vineland Adaptive Behavior Scales Second Edition Survey Forms Manual. AGS Publishing] and its psychome...