Abstract not found

this document. 9.5.2 A comparison of CUE and libido

This work presents a unied pattern-based epistemological framework, called a Knowledge Manifold, for the description and extraction of knowledge from information. Within this framework it also presents the metaphor of the Garden Of Knowledge as a constructive example. Any type of KM is defined in terms of its objective calibration protocols - procedures that are implemented on top of the participating subjective knowledge-patches. They are the procedures of agreement and obedience that characterize the coherence of any type of interaction, and which are used here in order to formalize the concept of participator consciousness in terms of the inverse-direct limit duality of Category Theory.

Machine Due to the current technology of the computers we can use, we have chosen an extremely abridged emulation of the machine that will effectively run the programs, instead of more proper languages, like l-calculus (or LISP). We have adapted the "toy RISC" machine of [Hernndez & Hernndez 1993] with two remarkable features inherited from its object-oriented coding in C++: it is easily tunable for our needs, and it is efficient. We have made it even more reduced, removing any operand in the instruction set, even for the loop operations. We have only three registers which are AX (the accumulator), BX and CX. The operations Q b we have used for our experiment are in Table 1: LOOPTOP Decrements CX. If it is not equal to the first element jump to the program top.

The concept of emergent “levels ” (i.e. levels that arise from interactions of objects at lower levels) is fundamental to scientific theory. In this paper, we argue for an expanded role for this concept of “levels ” in the study of science. We show that confusion of levels (and “slippage ” between levels) is the source of many deep misunderstandings about patterns and phenomena in the world. These misunderstandings are evidenced not only in students ’ difficulties in the formal study of science but also in their misconceptions about experiences in their everyday lives. The StarLogo modeling language is designed as a medium for students to build models of multi-leveled phenomena and through these constructions explore the concept of levels. We describe several case studies of students working in StarLogo. The cases illustrate students ’ difficulties with the concept of levels, and how they can begin to develop richer understandings.

There are five fundamental concerns in the synthesis of realistic imagery of fractal landscapes: 1) convincing geometric models of terrain; 2) efficient algorithms for rendering those potentially-large terrain models; 3) atmospheric effects, or aerial perspective, to provide a sense of scale; 4) surface textures as models of natural phenomena such as clouds, water, rock strata, and so forth, to enhance visual detail in the image beyond what can be modelled geometrically; and 5) a global context in which to situate the scenes. Results in these five areas are presented, and some aspects of the development of computer graphics as a new process and medium for the fine arts are discussed. Heterogeneous terrain models are introduced, and preliminary experiments in simulating fluvial erosion are presented to provide fractal drainage network features. For imaging detailed terrain models we describe grid tracing, a time- and memory-efficient algorithm for ray tracing height fields. To obtain aerial perspective we develop geometric models of aerosol density distributions with efficient integration schemes for determining scattering and extinction, and an efficient Rayleigh scattering approximation. We also describe physically-based models of the rainbow and mirage. Proceduralism is an underlying theme of this work; this is the practice of abstracting models of complex form and behaviors into relatively terse algorithms, which are evaluated in a lazy fashion. Procedural textures are developed as models of natural phenomena such as mountains and clouds, culminating a procedural model of an Earth-like planet which in the future may be explored interactively in a virtual reality setting.

This paper introduces ATNoSFEERS, a model aimed at designing evolutive and adaptive behaviors for agents or multi-agent systems. We first discuss briefly the main problems raised by classical evolutionary models, which are not intended to produce agents or behaviors but to solve problems. Then we provide detailed explanations about the model we propose and its components. We also show through a simple example how the system works, and give some experimental results. Finally, we discuss the features of our model and propose extensions.

A myth has arisen concerning Turing's paper of 1936, namely that Turing set forth a fundamental principle concerning the limits of what can be computed by machine - a myth that has passed into cognitive science and the philosophy of mind, to wide and pernicious effect. This supposed principle, sometimes incorrectly termed the 'Church-Turing thesis', is the claim that the class of functions that can be computed by machines is identical to the class of functions that can be computed by Turing machines. In point of fact Turing himself nowhere endorses, nor even states, this claim (nor does Church). I describe a number of notional machines, both analogue and digital, that can compute more than a universal Turing machine. These machines are exemplars of the class of nonclassical computing machines. Nothing known at present rules out the possibility that machines in this class will one day be built, nor that the brain itself is such a machine. These theoretical considerations undercut a numb...

this paper a Shackleton, page 2

Abstract. Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) entities interacting locally with their environment cause coherent functional global patterns to emerge. SI provides a basis with which it is possible to explore collective (or distributed) problem solving without centralized control or the provision of a global model. To tackle the formation of a coherent social collective intelligence from individual behaviors, we discuss several concepts related to self-organization, stigmergy and social foraging in animals. Then, in a more abstract level we suggest and stress the role played not only by the environmental media as a driving force for societal learning, as well as by positive and negative feedbacks produced by the many interactions among agents. Finally, presenting a simple model based on the above features, we will address the collective adaptation of a social community to a cultural (environmental, contextual) or media informational dynamical landscape, represented here – for the purpose of different experiments – by several three-dimensional mathematical functions that suddenly change over time. Results indicate that the collective intelligence is able to cope and quickly adapt to unforeseen situations even when over the same cooperative foraging period, the community is requested to deal with two different and contradictory purposes. 1