M3 “LEARNING IN RANDOM ENVIRONMENTS”
Horario: 9 a 12 hs.
PROFESOR: Dr. B. John Oommen.
Es Doctor en Ingeniería Eléctrica de la Universidad Purdue, USA. Actualmente es profesor de la School of Computer Science, Carleton University, Ottawa. Tiene más de cien publicaciones, capítulos de libros y presentaciones en congresos sobre los siguientes temas: Sistemas de Aprendizaje, Búsqueda y Almacenamiento de Datos, Algoritmos Geométricos, Pattern Recognition, Robótica, Estructuras de Datos Adaptativas, entre otros.
PROGRAMA:
This course will introduce the students to computerized adaptive learning techniques which can be utilized when dealing with a random enviroment. Initially, mathematical tools suchs as Markov chains and the solution of difference equations will be reviewed. Then, learning models in mathematical psychology will be discussed. The heart of the course will involve deterministic and stochastic learning automata, variable structure stochastic automata, operation in random enviroments, norms of learning, linear and nolinear learning schemes with ergodic and no-ergodic properties. The most recent discretized and estimator algorithms will also be studied. Applications of learning automata in telephone routing, file allocations, game playing, path finding, optimization and decision making will be discussed.
PREREQUISITOS:
Nociones básicas de Probabilidades y Estadística.
Este curso se dictará en inglés
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