Hanoi, Vietnam. November 2-8, 2024.
ISSN: 2334-1033
ISBN: 978-1-956792-05-8
Copyright © 2024 International Joint Conferences on Artificial Intelligence Organization
Planning and acting under the presence of exogenous events brings a number of challenges as events might modify the environment without the consent of the acting agent. Consequently, the agent's plan might get disrupted, agent's goals might no longer be achievable, or, worse, the agent might suffer some damage (e.g. damage to the robot). Although policies, mapping states to appropriate actions to take, can describe, in theory, how the agent should act, they might be difficult to explain and understand for humans in the loop.
In this paper, we describe the concept of robust plans that are sequences of actions that can be successfully executed regardless of event occurrence. Robust plans are easier to understand (than policies). We present two methods for verifying whether a sequence of actions is a robust plan, one based on compilation to classical planning, and the other based on leveraging delete-relaxation. We also present a method for generating robust plans that is derived from the "relaxation" verification method. The methods are evaluated on three domains.