Fuzzy Logic in Artificial Intelligence Towards Intelligent Systems IJCAI '95 Workshop Montréal, Canada, August 19–21, 1995 Selected Papers / [electronic resource] :
edited by Trevor P. Martin, Anca L. Ralescu.
- Berlin, Heidelberg : Springer Berlin Heidelberg, 1997.
- X, 282 p. online resource.
- Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 1188 0302-9743 ; .
- Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 1188 .
Constructing prioritized fuzzy models -- Integrating activities with neurofuzzy distributed systems -- The use of fuzzy representation in a CBR system for mesh design -- FLIP++ a fuzzy logic inference processor library -- Fuzzy reasoning and applications for intelligent scheduling of robots -- Fuzzy Logic as interfacing technique in hybrid AI-systems -- Extracting knowledge from data using an intelligent fuzzy data browser -- Fuzzy systems with learning capability -- Automatic knowledge base tuning -- A fuzzy-based approach to the analysis of financial investments -- Searching for the organizational memory using fuzzy modeling -- Fuzzy geodesic distance in images -- Using fuzzy information in knowledge guided segmentation of brain tumors -- FEDGE — Fuzzy edge detection by Fuzzy Categorization and Classification of edges -- Towards hybrid spatial reasoning -- Mobile robot localization using fuzzy maps -- Structure cognition from images -- Towards possibilistic decision theory -- Measurement-theoretic frameworks for fuzzy set theory -- A resemblance approach to analogical reasoning functions.
This thoroughly refereed and well organized collection of papers is largely based on papers originally presented at the IJCAI'95 Workshop on Fuzzy Logic in AI, held in Montreal, Canada, in August 1995. Additionally, a few papers were invited in order to round off the scope and competent coverage of relevant topics. The 20 revised full papers included are organized in sections on hybrid and novel architectures, machine learning and data mining, image processing and computer vision, and theoretical developments. Focusing on the most pressing problems of AI, the volume supports the view that fuzzy systems combined with traditional AI leads the move towards the next generation of intelligent systems.
9783540497325
10.1007/3-540-62474-0 doi
Computer science.
Artificial intelligence.
Computer Science.
Artificial Intelligence (incl. Robotics).
Mathematical Logic and Formal Languages.
Control Engineering.
Q334-342 TJ210.2-211.495
006.3
Constructing prioritized fuzzy models -- Integrating activities with neurofuzzy distributed systems -- The use of fuzzy representation in a CBR system for mesh design -- FLIP++ a fuzzy logic inference processor library -- Fuzzy reasoning and applications for intelligent scheduling of robots -- Fuzzy Logic as interfacing technique in hybrid AI-systems -- Extracting knowledge from data using an intelligent fuzzy data browser -- Fuzzy systems with learning capability -- Automatic knowledge base tuning -- A fuzzy-based approach to the analysis of financial investments -- Searching for the organizational memory using fuzzy modeling -- Fuzzy geodesic distance in images -- Using fuzzy information in knowledge guided segmentation of brain tumors -- FEDGE — Fuzzy edge detection by Fuzzy Categorization and Classification of edges -- Towards hybrid spatial reasoning -- Mobile robot localization using fuzzy maps -- Structure cognition from images -- Towards possibilistic decision theory -- Measurement-theoretic frameworks for fuzzy set theory -- A resemblance approach to analogical reasoning functions.
This thoroughly refereed and well organized collection of papers is largely based on papers originally presented at the IJCAI'95 Workshop on Fuzzy Logic in AI, held in Montreal, Canada, in August 1995. Additionally, a few papers were invited in order to round off the scope and competent coverage of relevant topics. The 20 revised full papers included are organized in sections on hybrid and novel architectures, machine learning and data mining, image processing and computer vision, and theoretical developments. Focusing on the most pressing problems of AI, the volume supports the view that fuzzy systems combined with traditional AI leads the move towards the next generation of intelligent systems.
9783540497325
10.1007/3-540-62474-0 doi
Computer science.
Artificial intelligence.
Computer Science.
Artificial Intelligence (incl. Robotics).
Mathematical Logic and Formal Languages.
Control Engineering.
Q334-342 TJ210.2-211.495
006.3