Mobile Agent Planning Problems 1998 Trustees of Dartmouth College for My Grandfather Seiichi Moizumi

Mobile agents have received much attention recently as a way to e ciently access distributed resources in a low bandwidth network. Planning allows mobile agents to make the best use of the available resources. This thesis studies several planning problems that arise in mobile agent information retrieval and data-mining applications. The general description of the planning problems is as follows: We are given sites at which a certain task might be successfully performed. Each site has an independent probability of success associated with it. Visiting a site and trying the task there requires time (or some other cost matrix) regardless of whether the task is completed successfully or not. Latencies between sites, that is, the travel time between those two sites also have to be taken into account. If the task is successfully completed at a site then the remaining sites need not be visited. The planning problems involve nding the best sequence of sites to be visited, which minimizes the expected time to complete the task. We name the problems Traveling Agent Problems due to their analogy with the Traveling Salesman Problem. This Traveling Agent Problem is NP complete in the general formulation. However, in this thesis a polynomial-time algorithm has been successfully developed to solve the problem by adding a realistic assumption to it. The assumption enforces the fact that the network consists of subnetworks where latencies between machines in the same subnetwork are constant while latencies between machines located in di erent subnetworks vary. Di erent versions of the Traveling Agent Problem are considered: (1) single agent problems, (2) multiple agent problems (multiple agents cooperate to complete the same task) and (3) deadline problems (single or multiple agents need to complete a task without violating a deadline constraint at each location in the network). Polynomial and pseudo-polynomial algorithms for these problems have been developed in this thesis. In addition to the theory and algorithm development for the various Traveling Agent Problems, a planning system that uses these algorithms was implemented. Descriptions of the mobile agent planning system with its supporting components such as network