Goal-Driven Autonomy with Case-Based Reasoning

The vast majority of research on AI planning has focused on automated plan recognition, in which a planning agent is provided with a set of inputs that include an initial goal (or set of goals). In this context, the goal is presumed to be static; it never changes, and the agent is not provided with the ability to reason about whether it should change this goal. For some tasks in complex environments, this constraint is problematic; the agent will not be able to respond to opportunities or plan execution failures that would benefit from focusing on a different goal. Goal driven autonomy (GDA) is a reasoning framework that was recently introduced to address this limitation; GDA systems perform anytime reasoning about what goal(s) should be satisfied [4]. Although promising, there are natural roles that case-based reasoning (CBR) can serve in this framework, but no such demonstration exists. In this paper, we describe the GDA framework and describe an algorithm that uses CBR to support it...

• Type: Conference
• Year: 2010
• Where: ICCBR
• Authors: Héctor Muñoz-Avila, Ulit Jaidee, David W. Aha, Elizabeth Carter
• Keywords: Automated Reasoning, GDA Framework, Goal Driven Autonomy, ICCBR 2010, Initial Goal