Learning and planning are two important topics of artificial intelligence. Learning deals with the algorithmic processes that make a computing machine able to “learn” and improve its performance during the process of complex tasks. Planning on the other hand, deals with decision and construction processes that make a machine capable of constructing an intelligent plan for the solution of a particular complex problem.This book combines both learning and planning methodologies and their applications in different domains. It is divided into two parts. The first part contains seven chapters on the ongoing research work in symbolic and connectionist learning. The second part includes seven chapters which provide the current research efforts in planning methodologies and their application to robotics.

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Theory and Method in Higher Education Research, provides a forum specifically for higher education researchers to discuss issues of theory and method. This latest volume presents a truly international approach with contributions from Argentina, Belgium, Canada, the Czech Republic, Finland, Germany, Norway, Portugal, the U.K. and the U.S.

American national trade bibliography.