Axiomatic foundation of the analytic hierarchy process
Management Science
SOAR: an architecture for general intelligence
Artificial Intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Ordinal information and preference structures: decision models and applications
Ordinal information and preference structures: decision models and applications
Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
International Journal of Computer Vision
Agents that reduce work and information overload
Communications of the ACM
Training agents to perform sequential behavior
Adaptive Behavior
Fuzzy Systems as Universal Approximators
IEEE Transactions on Computers
Integrating reactive, sequential, and learning behavior using dynamical neural networks
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Designing conventions for automated negotiation
AI Magazine
Wavelets and subband coding
Multimedia Systems - Special issue on content-based retrieval
CORE: a content-based retrieval engine for multimedia information systems
Multimedia Systems - Special issue on content-based retrieval
Artificial life meets entertainment: lifelike autonomous agents
Communications of the ACM
Fuzzy engineering
Multimedia Information Systems
IEEE MultiMedia
IEEE Transactions on Pattern Analysis and Machine Intelligence
Natural Negotiation for Believable Agents
Natural Negotiation for Believable Agents
The ALIVE system: wireless, full-body interaction with autonomous agents
Multimedia Systems - Special issue on multimedia and multisensory virtual worlds
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
Adaptive fuzzy priors for Bayesian inference
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
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A neural fuzzy system can learn an agent profile of a user when it samples user question-answer data. A fuzzy system uses if-then rules to store and compress the agent's knowledge of the user's likes and dislikes. A neural system uses training data to form and tune the rules. The profile is a preference map or a bumpy utility surface defined over the space of search objects. Rules define fuzzy patches that cover the surface bumps as learning unfolds and as the fuzzy agent system gives a finer approximation of the profile. The agent system searches for preferred objects with the learned profile and with a new fuzzy measure of similarity. The appendix derives the supervised learning law that tunes this matching measure with fresh sample data. We test the fuzzyagent profile system on object spaces of flowers and sunsets and test the fuzzy agent matching system on an object space of sunset images. Rule explosion and data acquisition impose fundamental limits on the system designs.