Proceedings, Volumes 1-2IEEE, 1999 - Artificial intelligence |
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Page 159
REINFORCEMENT LEARNING AND AUTOMATIC CATEGORIZATION Josep M Porta and Enric Celaya Institut de Robōtica i Informātica Industrial ( UPC - CSIC ) , c / Gran Capitā 2-4 , Edifici NEXUS , Planta 2 08034 , Barcelona ( SPAIN ) T. + 34 93 401 ...
REINFORCEMENT LEARNING AND AUTOMATIC CATEGORIZATION Josep M Porta and Enric Celaya Institut de Robōtica i Informātica Industrial ( UPC - CSIC ) , c / Gran Capitā 2-4 , Edifici NEXUS , Planta 2 08034 , Barcelona ( SPAIN ) T. + 34 93 401 ...
Page 160
... learning algorithms . The categorization process can be the most difficult stage of the solution of a task ( the proper interpretation of the sensor readings can transform an apparently complex task in a simple one ) so , if it is done ...
... learning algorithms . The categorization process can be the most difficult stage of the solution of a task ( the proper interpretation of the sensor readings can transform an apparently complex task in a simple one ) so , if it is done ...
Page 166
Taking into account the history of reinforcement learning we can say that our system goes a step further than the usual reinforcement learning algorithms . The first algorithms to learn through reinforcement were developed in the ...
Taking into account the history of reinforcement learning we can say that our system goes a step further than the usual reinforcement learning algorithms . The first algorithms to learn through reinforcement were developed in the ...
Contents
Java RealTime Distributed Processing Over ATM Networks with ChorusOS | 3 |
Optimizing Costs and Processing Times Under Variable External Processing | 4 |
A Petri Net Solution to the Problem of Deadlocks in Systems of Processes With | 8 |
Copyright | |
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action activity actuators adaptive agent algorithm APDU applet application architecture Automation behavior byte camera client components Computer Vision configuration constraints control system CORBA cost defined described detected developed devices distributed dynamic environment error example execution feature Figure filter FPGA function fuzzy Genetic Algorithms graph hardware IEEE implementation industrial initial input integrated interface Java JavaCard laser Lonworks machine manipulator manufacturing system marked graph matrix method mobile robot module monitoring neural network nodes object obstacle obtained OpenCard Framework operations optimal output parameters PC/SC performance Petri net pixel position problem proposed real-time reinforcement learning rules scheduling sensor sequence server signal simulation smart card solution strategy structure Sun Microsystems task techniques terminal application tool trajectory transducers transition ultrasonic variables vector virtual visual VRML workflow