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Scientific discovery: computational explorations of the creative process
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Variable precision rough set model
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Basic proof theory
Tolerance approximation spaces
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Knowledge representation: logical, philosophical and computational foundations
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Rough set methods and applications: new developments in knowledge discovery in information systems
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Quantum computing
Strategic negotiation in multiagent environments
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Autonomous agents and multi-agent systems: explorations in learning, self-organization and adaptive computation
Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer
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Rough Sets: Theoretical Aspects of Reasoning about Data
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Genetic Algorithms in Search, Optimization and Machine Learning
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Modern Information Retrieval
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Spidering Hacks
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Concept Data Analysis: Theory and Applications
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A Semantic Web Primer
Automated Planning: Theory & Practice
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Knowledge Representation and Reasoning
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Handbook on Ontologies (International Handbooks on Information Systems)
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Explorer's Guide to the Semantic Web
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Text Mining: Predictive Methods for Analyzing Unstructured Information
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A cognitive substrate for achieving human-level intelligence
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Fundamenta Informaticae - Concurrency Specification and Programming (CS&P 2003)
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PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
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PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Behavioral pattern identification through rough set modelling
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IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
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Toward perception based computing: a rough-granular perspective
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Transactions on Rough Sets XI
Interactive information systems: Toward perception based computing
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Rough Set Based Reasoning About Changes
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
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The problem considered in this article is how does one go about discovering and designing intelligent systems. The solution to this problem is considered in the context of what is known as wisdom technology (wistech), an important computing and reasoning paradigm for intelligent systems. A rough-granular approach to wistech is proposed for developing one of its possible foundations. The proposed approach is, in a sense, the result of the evolution of computation models developed in the Rasiowa-Pawlak school. We also present a long-term program for implementation of what is known as a wisdom engine. The program is defined in the framework of cooperation of many Research & Development (R & D) institutions and is based on a wistech network (WN) organization.