Compute-intensive methods in artificial intelligence

In order to deal with the inherent combinatorial nature of many tasks in ar tificial intelligence, domain-specific knowledge has been used to control s earch and reasoning or to eliminate the need for general inference altogeth er. However, the process of acquiring domain knowledge is an important bott leneck in the use of such "knowledge-intensive" methods. Compute-intensive methods, on the other hand, use extensive search and reasoning strategies t o limit the need for detailed domain-specific knowledge. The idea is to der ive much of the needed information from a relatively compact formalization of the domain under consideration. Up until recently, such general reasonin g strategies were much too expensive for use in applications of interesting size but recent advances in reasoning and search methods have shown that c ompute-intensive methods provide a promising alternative to knowledge-inten sive methods.