Abstract
In this article we analyze a particular model of control among intelligent agents, that ofnon-absolute control. Non-absolute control involves a “supervisor” agent that issues orders to a “subordinate” agent. An example might be a human agent on Earth directing the activities of a Mars-based semi-autonomous vehicle.
Both agents operate with essentially the same goals. The subordinate agent, however, is assumed to have access to some information that the supervisor does not have. The agent is thus expected to exercise its judgment in following orders (i.e., following the true intent of the supervisor, to the best of its ability). After presenting our model, we discuss the planning problem: how would a subordinate agent choose among alternative plans? Our solutions focus on evaluating the distance between candidate plans, and is appropriate to any scenario in which one agent wants to follow (as much as possible) another agent's plan.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Arkin, E., L.P. Chew, D.P. Huttenlocher, K. Kedem, and J.S.B. Mitchell. (1990). “An Efficiently Computable Metric for Comparing Polygonal Shapes.” InProceedings of the First ACM-SIAM Symposium on Discrete Algorithms.
Atallah, M.J. (1983). “A Linear Time Algorithm for the Hausdorff Distance Between Convex Polygons.”Information Processing Letters 17, 207–209.
Chapman, D. (1987). “Planning for Conjunctive Goals.”Artificial Intelligence 32(3), 333–377.
Conway, Lynn, Richard A. Volz, and Michael W. Walker. (1990). “Teleautonomous Systems: Projecting and Coordinating Intelligent Action at a Distance.”IEEE Transactions on Robotics and Automation 6(2), 146–158.
Durfee, E.H., and V.R. Lesser. (1987). “Using Partial Global Plans to Coordinate Distributed Problem Solvers.” InProceedings of the Tenth International Joint Conference on Artificial Intelligence, Milan, pp. 875–883.
Durfee, Edmund H. (1988).Coordination of Distributed Problem Solvers. Boston: Kluwer Academic Publishers.
Ephrati, Eithan, and Jeffrey S. Rosenschein. (1991). “Non-Absolute Control Among Intelligent Agents: Preliminary Report.” InProceedings of the Eighth Israeli Symposium on Artificial Intelligence and Computer Vision, Ramat Gan, Israel, pp. 155–179.
Ephrati, Eithan, and Jeffrey S. Rosenschein. (1992). “Multi-Agent Planning as Search for a Consensus that Maximizes Social Welfare.” InPre-Proceedings of the Fourth European Workshop on Modeling Autonomous Agents in a Multi-Agent World, Rome, Italy.
Finger, J.J. (1986). “Exploiting Constraints in Design Synthesis.” Ph.D. Dissertation, Stanford University, Stanford, CA.
Genesereth, Michael R., Matthew L. Ginsberg, and Jeffrey S. Rosenschein. (1986). “Cooperation without Communication.” InProceedings of the National Conference on Artificial Intelligence, Philadelphia, Pennsylvania, pp. 51–57.
Ginsberg, Matthew L. (1986). “Possible Worlds Planning.” In M. Georgeff and A. Lansky (eds.).Reasoning about Actions and Plans. Los Altos, CA: Morgan Kaufmann Publishers, pp. 213–243.
Halpern, Joseph Y., and Yoram Moses. (1984). “Knowledge and Common Knowledge in a Distributed Environment.” InProceedings of the Third ACM Conference on Principles of Distributed Computing, pp. 50–61.
Holmstorm, B., and P. Milgrom. (1991). “Multitask Principal-Agent Analyses: Incentive Contracts, Asset Ownership, and Job Design.”The Journal of Law, Economics and Organization 7, 24–52.
Katz, Matthew J., and Jeffrey S. Rosenschein. (1993). “Verifying Plans for Multiple Agents.”Journal of Experimental and Theoretical Artificial Intelligence, forthcoming.
Konolige, Kurt. (1982). “A First-Order Formalization of Knowledge and Action for a Multi-Agent Planning System.”Machine Intelligence 10.
Kraus, Sarit, Eithan Ephrati, and Daniel Lehmann. (1991). “Negotiation in a Non-Cooperative Environment.”Journal of Experimental and Theoretical Artificial Intelligence 3(4), 255–282.
Lesser, Victor R. (1987). “Distributed Problem Solving.” In Stuart C. Shapiro (ed.),Encyclopedia of Artificial Intelligence. New York: John Wiley and Sons, pp. 245–251.
Malone, Thomas W., Richard E. Fikes, and M.T. Howard. (1988). “Enterprise: A Market-Like Task Scheduler for Distributed Computing Environments.” In B.A. Huberman (ed.),The Ecology of Computation. Amsterdam: North-Holland Publishing Company, pp. 177–205.
Malone, Thomas W. (1986). “Organizing Information Processing Systems: Parallels Between Human Organizations and Computer Systems.” In W. Zacharai, S. Robertson, and J. Black (eds.),Cognition, Computation, and Cooperation. Norwood, NJ: Ablex Publishing Corp.
Rosenschein, Jeffrey S. (1982). “Synchronization of Multi-Agent Plans.” InProceedings of the National Conference on Artificial Intelligence, Pittsburgh, PA, pp. 115–119.
Sycara, Katia P. (1988). “Resolving Goal Conflicts via Negotiation.” InProceedings of the Seventh National Conference on Artificial Intelligence, St. Paul, Minnesota, pp. 245–250.
Sycara, Katia P. (1989). “Argumentation: Planning Other Agents' Plans.” InProceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI, pp. 517–523.
Zlotkin, Gilad, and Jeffrey S. Rosenschein. (1991). “Incomplete Information and Deception in Multi-Agent Negotiation.” InProceedings of the Twelfth International Joint Conference on Artificial Intelligence, Sydney, Australia, pp. 225–231.
Author information
Authors and Affiliations
Additional information
This is a revised and expanded version of the paper “Constrained Intelligent Action: Planning Under the Influence of a Master Agent” that appeared in the Tenth National Conference on Artificial Intelligence, San Jose, California, July 1992.
Rights and permissions
About this article
Cite this article
Ephrati, E., Rosenschein, J.S. Planning to please: Following another agent's intended plan. Group Decis Negot 2, 219–235 (1993). https://doi.org/10.1007/BF01384247
Issue Date:
DOI: https://doi.org/10.1007/BF01384247