|Title||Case-based behavior recognition to facilitate planning in unmanned air vehicles|
|Publication Type||Conference Proceedings|
|Year of Conference||2014|
|Authors||Borck, H, Karneeb, J, Alford, R, Aha, DW|
|Conference Name||Case-Based Agents: Papers from the ICCBR Workshop.|
|Publisher||University College Cork|
|Conference Location||Cork, Ireland|
An unmanned air vehicle (UAV) can operate as a capable team member in mixed human-robot teams if the agent that controls it can intelligently plan. However, planning effectively in an air combat scenario requires understanding the behaviors of hostile agents in that scenario, which is challenging in partially observable environments such as the one we study. We present a Case-Based Behavior Recognition (CBBR) algorithm that annotates an agent’s behaviors using a discrete feature set derived from a continuous spatio-temporal world state. These behaviors can then be given as input to an air combat simulation, along with the UAV’s plan, to predict hostile actions and determine the effectiveness of the given plan. We describe an initial implementation of a CBBR prototype in the context of a goal reasoning agent designed for UAV control.