Abstract planning in dynamic environments

Abstract

Solving problems in dynamic and heterogeneous environments where information sources change their format representation and stored data is very complex. In previous work we presented a system called MAPWeb (Multiagent Planning on the Web) that tried to solve these problems by integrating artificial intelligence planning techniques within the multiagent framework. Basically, MAPWeb allows cooperative work between planning agents and Web agents. The purpose of MAPWeb is to find solutions to travel problems. In order to give detailed solutions, MAPWeb uses information gathering techniques to retrieve travel information that is made available by many different companies. However, Web access to the information sources is quite time expensive. In this paper, we try to minimize the number of Web queries by using caching techniques based on relational databases. Experimental results show that the reduction in Web access time is quite important, while maintaining the number of solutions found.