Unreduced Dynamic Complexity: Towards the Unified Science of Intelligent Communication Networks and Software

Operation of autonomic communication networks with complicated user-oriented functions should be described as unreduced many-body interaction process. The latter gives rise to complex-dynamic behaviour including fractally structured hierarchy of chaotically changing realisations. We recall the main results of the universal science of complexity (http://cogprints.org/4471/) based on the unreduced interaction problem solution and its application to various real systems, from nanobiosystems (http://cogprints.org/4527/) and quantum devices to intelligent networks (http://cogprints.org/4114/) and emerging consciousness (http://cogprints.org/3857/). We concentrate then on applications to autonomic communication leading to fundamentally substantiated, exact science of intelligent communication and software. It aims at unification of the whole diversity of complex information system behaviour, similar to the conventional, "Newtonian" science order for sequential, regular models of system dynamics. Basic principles and first applications of the unified science of complex-dynamic communication networks and software are outlined to demonstrate its advantages and emerging practical perspectives

Why it is important to build robots capable of doing science

Science, like any other cognitive activity, is grounded in the sensorimotor interaction of our bodies with the environment. Human embodiment thus constrains the class of scientific concepts and theories which are accessible to us. The paper explores the possibility of doing science with artificial cognitive agents, in the framework of an interactivist-constructivist cognitive model of science. Intelligent robots, by virtue of having different sensorimotor capabilities, may overcome the fundamental limitations of human science and provide important technological innovations. Mathematics and nanophysics are prime candidates for being studied by artificial scientists

Assessment of Biology Majors’ Versus Nonmajors’ Views on Evolution, Creationism, and Intelligent Design

The controversy around evolution, creationism, and intelligent design resides in a historical struggle between scientific knowledge and popular belief. Four hundred seventy-six students (biology majors n=237, nonmajors n=239) at a secular liberal arts private university in Northeastern United States responded to a five-question survey to assess their views about: (1) evolution, creationism, and intelligent design in the science class; (2) students’ attitudes toward evolution; (3) students’ position about the teaching of human evolution; (4) evolution in science exams; and (5) students’ willingness to discuss evolution openly. There were 60.6% of biology majors and 42% of nonmajors supported the exclusive teaching of evolution in the science class, while 45.3% of nonmajors and 32% of majors were willing to learn equally about evolution, creationism, and intelligent design (question 1); 70.5% of biology majors and 55.6% of nonmajors valued the factual explanations evolution provides about the origin of life and its place in the universe (question 2); 78% of the combined responders (majors plus nonmajors) preferred science courses where evolution is discussed comprehensively and humans are part of it (question 3); 69% of the combined responders (majors plus nonmajors) had no problem answering questions concerning evolution in science exams (question 4); 48.1% of biology majors and 26.8% of nonmajors accepted evolution and expressed it openly, but 18.2% of the former and 14.2% of the latter accepted evolution privately; 46% of nonmajors and 29.1% of biology majors were reluctant to comment on this topic (question 5). Combined open plus private acceptance of evolution within biology majors increased with seniority, from freshman (60.7%) to seniors (81%), presumably due to gradual exposure to upper-division biology courses with evolutionary content. College curricular/pedagogical reform should fortify evolution literacy at all education levels, particularly among nonbiologists

An Intelligent Tutoring System for Teaching the 7 Characteristics for Living Things

Recently, due to the rapid progress of computer technology, researchers develop an effective computer program to enhance the achievement of the student in learning process, which is Intelligent Tutoring System (ITS). Science is important because it influences most aspects of everyday life, including food, energy, medicine, leisure activities and more. So learning science subject at school is very useful, but the students face some problem in learning it. So we designed an ITS system to help them understand this subject easily and smoothly by analyzing it and explaining it in a systematic way. In this paper, we describe the design of an Intelligent Tutoring System for teaching science for grade seven to help students know the 7 characteristics for living things smoothly. The system provides all topics of living things and generates some questions for each topic and the students should answer these questions correctly to move to the next level. In the result of an evaluation of the ITS, students like the system and they said that it is very useful for them and for their studies

Analyze of the Measuring Performance for Artificially Business Intelligent Systems

This paper analyzes the measuring performance of artificially business intelligent systems. Thousands of persons-years have been devoted to the research and development in the vari¬ous aspects of artificially intelligent systems. Much progress has been attained. However, there has been no means of evaluating the progress of the field. How can we assess the cur¬rent state of the science? Most of business intelligent systems are beginning to be deployed commercially. How can a commercial buyer evaluate the advantages and disadvantages of the intelligent candidate and decide which system will perform best for their business applica¬tion? If constructing a system from existing components, how does one select the one that is most appropriate within the desired business intelligent systems? The ability to measure the capabilities of business intelligent systems or components is more that an exercise in satisfy¬ing intellectual or philosophical curiosity. Without measurements and subsequent quantitative evaluation, it is difficult to gauge progress. It is both in a spirit of scientific enquiry and for pragmatic motivations that we embark on the quest for metrics for performance and intelli¬gence of business intelligent systems.artificially intelligent systems, analyze of the measuring performance, business intelligent systems, metrics for performance, meas¬urement performance