TY - GEN
T1 - Optimal agent selection
AU - Özcan, Fatma
AU - Subrahmanian, V. S.
AU - Golubchik, Leana
N1 - Funding Information:
This work was supported by the Army Research Lab under contract number DAAL0197K0135, the Army Research Office under grant number DAAD190010484, by DARPA/RL contract number F306029910552 and by National Science Foundation grant CCR-98-96232.
Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2001.
PY - 2001
Y1 - 2001
N2 - The Internet contains a vast array of sources that provide identical or similar services. When an agent needs to solve a problem, it may split the problem into “subproblems” and find an agent to solve each of the subproblems. Later, it may combine the results of these subproblems to solve the original problem. In this case, the agent is faced with the task of determining to which agents to assign the subproblems. We call this the agent selection problem (ASP for short). Solving ASP is complex because it must take into account several different parameters. For instance, different agents might take different amounts of time to process a request. Different agents might provide varying “qualities” of answers. Network latencies associated with different agents might vary. In this paper, we first formalize the agent selection problem and show that it is NP-hard. We then propose a generic cost function that is general enough to take into account the costs of (i) network and server loads, (ii) source computations, and (iii) internal mediator costs. We then develop exact and heuristic based algorithms to solve the agent selection problem.
AB - The Internet contains a vast array of sources that provide identical or similar services. When an agent needs to solve a problem, it may split the problem into “subproblems” and find an agent to solve each of the subproblems. Later, it may combine the results of these subproblems to solve the original problem. In this case, the agent is faced with the task of determining to which agents to assign the subproblems. We call this the agent selection problem (ASP for short). Solving ASP is complex because it must take into account several different parameters. For instance, different agents might take different amounts of time to process a request. Different agents might provide varying “qualities” of answers. Network latencies associated with different agents might vary. In this paper, we first formalize the agent selection problem and show that it is NP-hard. We then propose a generic cost function that is general enough to take into account the costs of (i) network and server loads, (ii) source computations, and (iii) internal mediator costs. We then develop exact and heuristic based algorithms to solve the agent selection problem.
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U2 - 10.1007/3-540-45422-5_2
DO - 10.1007/3-540-45422-5_2
M3 - Conference contribution
AN - SCOPUS:84974733630
SN - 9783540454229
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 2
EP - 17
BT - KI 2001
A2 - Baader, Franz
A2 - Brewka, Gerhard
A2 - Eiter, Thomas
PB - Springer Verlag
T2 - Joint 24th German Conference on Artificial Intelligence and 9th Austrian Conference on Artificial Intelligence, KI 2001
Y2 - 19 September 2001 through 21 September 2001
ER -