This model was implemented and tested on a variant of "Chinese Checkers. The learning process requires no external guidance or assistance. The model enables such a system to enhance and improve its playing capabilities through the use of a learning mechanism which extracts knowledge from actual playing experience. A theoretical model for a system that learns from its own experience in playing board games is presented in Learning from Experience in Board Games by Ze'ev Ben-Porat and Martin Golumbic. The articles in this book represent a selection of contributions presented at recent AI conferences held in Israel. This is equally true in Israel which has hosted several international forums on these topics. At national and international symposia as well as in research centers and universities all over the world, these subjects have been the focus of intense debate and study. Research in artificial intelligence, natural language processing and knowledge-based systems has blossomed during the past decade.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |