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Modelling and Reasoning with Vague Concepts
This volume introduces a formal representation framework for modelling and reasoning, that allows us to quantify the uncertainty inherent in the use of vague descriptions to convey information between intelligent agents. This can then be applied across a range of applications areas in automated reasoning and learning. The utility of the framework is demonstrated by applying it to problems in data analysis where the aim is to infer effective and informative models expressed as logical rules and relations involving vague concept descriptions. The author also introduces a number of learning algorithms within the framework that can be used for both classification and prediction (regression) problems. It is shown how models of this kind can be fused with qualitative background knowledge such as that provided by domain experts. The proposed algorithms will be compared with existing learning methods on a range of benchmark databases such as those from the UCI repository.
Logical Foundations for Rule-Based Systems
The book presents logical foundations for rule-based systems. An attempt has been made to provide an in-depth discussion of logical and other aspects of such systems, including languages for knowledge representation, inference mechanisms, inference control, design and verification. The ultimate goal was to provide a deeper theoretical insight into the nature of rule-based systems and put together the most complete presentation including details so frequently skipped in typical textbooks. The book may be useful to potentially wide audience, but it is aimed at providing specific knowledge for graduate, post-graduate and Ph.D. students, as well as knowledge engineers and research workers involved in the domain of AI. It also constitutes a summary of the Author’s research and experience gathered through several years of his research work.
Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Since 1991, the European Conference on Symbolic and Quantitative Appr- ches to Reasoning with Uncertainty (ECSQARU) has been a major forum for advances in the theory and practice of reasoning and decision making under - certainty. The scope of ECSQARU is wide and includes, but is not limited to, fundamental issues, representation, inference, learning, and decision making in qualitative and numeric paradigms. The ?rst ECSQARU conference (1991) was held in Marseilles, and since then it has been held in Granada (1993), Fribourg (1995), Bonn (1997), London (1999) and Toulouse (2001). This volume contains the papers that were presented at ECSQARU 2003, held at Aalborg University, Denmark, from Ju...
Modelling and Optimization of Biotechnological Processes
Mostindustrialbiotechnologicalprocessesareoperatedempirically.Oneofthe major di?culties of applying advanced control theories is the highly nonlinear nature of the processes. This book examines approaches based on arti?cial intelligencemethods,inparticular,geneticalgorithmsandneuralnetworks,for monitoring, modelling and optimization of fed-batch fermentation processes. The main aim of a process control is to maximize the ?nal product with minimum development and production costs. This book is interdisciplinary in nature, combining topics from biotechn- ogy, arti?cial intelligence, system identi?cation, process monitoring, process modelling and optimal control. Both simulation and experimenta...
Genetic Systems Programming
Designing complex programs such as operating systems, compilers, filing systems, data base systems, etc. is an old ever lasting research area. Genetic programming is a relatively new promising and growing research area. Among other uses, it provides efficient tools to deal with hard problems by evolving creative and competitive solutions. Systems Programming is generally strewn with such hard problems. This book is devoted to reporting innovative and significant progress about the contribution of genetic programming in systems programming. The contributions of this book clearly demonstrate that genetic programming is very effective in solving hard and yet-open problems in systems programming. Followed by an introductory chapter, in the remaining contributed chapters, the reader can easily learn about systems where genetic programming can be applied successfully. These include but are not limited to, information security systems, compilers, data mining systems, stock market prediction systems, robots and automatic programming.
Creative Space
Creative Space summarizes and integrates the various up-to-date approaches of computational intelligence to knowledge and technology creation including the specific novel feature of utilizing the creative abilities of the human mind, such as tacit knowledge, emotions and instincts, and intuition. It analyzes several important approaches of this new paradigm such as the Shinayakana Systems Approach, the organizational knowledge creation theory, in particular SECI Spiral, and the Rational Theory of Intuition – resulting in the concept of Creative Space. This monograph presents and analyzes in detail this new concept together with its ontology – the list and meanings of the analyzed nodes of this space and of the character of transitions linking these nodes.
A Geometry of Approximation
'A Geometry of Approximation' addresses Rough Set Theory, a field of interdisciplinary research first proposed by Zdzislaw Pawlak in 1982, and focuses mainly on its logic-algebraic interpretation. The theory is embedded in a broader perspective that includes logical and mathematical methodologies pertaining to the theory, as well as related epistemological issues. Any mathematical technique that is introduced in the book is preceded by logical and epistemological explanations. Intuitive justifications are also provided, insofar as possible, so that the general perspective is not lost. Such an approach endows the present treatise with a unique character. Due to this uniqueness in the treatmen...
Rough Sets
The volume LNAI 12179 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2020, which was due to be held in Havana, Cuba, in June 2020. The conference was held virtually due to the COVID-19 pandemic. The 37 full papers accepted were carefully reviewed and selected from 50 submissions. The papers are grouped in the following topical sections: general rough sets; three-way decision theory; attribute reduction; granular computing; formal concept analysis; data summarization; community detection; fuzzy cognitive maps; tutorials.
Communications and Discoveries from Multidisciplinary Data
This book collects selected papers by authors for CODATA 2006, which are relevant to the acquisition of knowledge and the assessment of risk and opportunity that comes from combining data from a number of different disciplines.
Scalable Uncertainty Management
This volume contains the papers presented at the Third International Conference on Scalable Uncertainty Management, SUM 2009, in Washington, DC, September 28-30, 2009. It contains 21 technical papers which were selected out of 30 submitted papers in a rigourous reviewing process. The volume also contains extended abstracts of two invited talks. The volume reflects the growing interest in uncertainty and incosistency and aims at bringing together all those interested in the management of uncertainty and inconsistency at large.
