|Title||Case-Based Parameter Selection for Plans: Coordinating Autonomous Vehicle Teams|
|Publication Type||Conference Proceedings|
|Year of Conference||2014|
|Authors||Auslander, B, Apker, T, Aha, DW|
|Conference Name||Proceedings of the Twenty-Second International Conference on Case-Based Reasoning|
|Conference Location||Cork, Ireland|
Executing complex plans for coordinating the behaviors of multiple heterogeneous agents often requires setting several parameters. For example, we are developing a decision aid for deploying a set of autonomous vehicles to perform situation assessment in a disaster relief operation. Our system, the Situated Decision Process (SDP), uses parameterized plans to coordinate these vehicles. However, no model exists for setting the values of these parameters. We describe a case-based reasoning solution for this problem and report on its utility in simulated scenarios, given a case library that represents only a small percentage of the problem space. We found that our agents, when executing plans generated using our case-based algorithm on problems with high uncertainty, performed significantly better than when executing plans using baseline approaches.
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