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Artificial Intelligence for Communications and Networks - 4th EAI International Conference, AICON 2022, Hiroshima, Japan, November 30 - December 1, 2022, Proceedings (1st ed. 2023)
Yasushi Kambayashi, Ngoc Thanh Nguyen, Shu-Heng Chen, Petre Dini, Munehiro Takimoto
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R1,609
Discovery Miles 16 090
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Ships in 12 - 17 working days
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This book, AICON 2022, constitutes the post-conference proceedings
of the 4th EAI International Conference on Artificial Intelligence
for Communications and Networks, AICON 2022, held in Hiroshima,
Japan, inĀ November 30- December 1, 2022. The 9 full papers
and 4 short papers were carefully reviewed and selected from 36
submissions. The papers detail research in the areas of AI and
communication systems related to intelligent systems and
computational intelligence for communication and networks. They are
organized in topical sections on AI and networks; machine learning;
and evolutionary computation.
Multi-Agent Applications with Evolutionary Computation and
Biologically Inspired Technologies: Intelligent Techniques for
Ubiquity and Optimization compiles numerous ongoing projects and
research efforts in the design of agents in light of recent
development in neurocognitive science and quantum physics. This
innovative collection provides readers with interdisciplinary
applications of multi-agents systems, ranging from economics to
engineering.
We have experienced different theories of software construction
paradigms in the last few decades; such as structured programming''
in the 1970's and "object-oriented programming" in the 1980's. The
object-oriented paradigm is considered a standard for many software
development activities, from the analysis phase to various support
phases. There is little quantitative research, however, regarding
the question whether object-oriented programming improves
productivity. Many assume that object-oriented programming is more
productive than traditional structured programming. This assumption
lacks concrete, empirical data that support such belief. This
dissertation identifies problems in the current object-oriented
programming practice, and then presents an alternative paradigm to
help overcome these problems. This paradigm separates the
declaration of data structures from program executable
instructions. We call this paradigm {\it the separation principle}.
We first tried to understand what this paradigm means in practice.
We developed example programs in a variety of application areas. We
found that the separation principle is a viable paradigm for
practical program construction. In order to demonstrate the
validity of this paradigm, we have conducted both theoretical and
empirical studies. The theoretical study consists of complexity
measurements. The empirical study constitutes human understanding
measurement; its purpose is to show statistical significance. The
results give evidence of the effectiveness of the separation
principle for practical software construction.
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