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Assessing whether an agent has abandoned a goal or is actively pursuing it isimportant when multiple agents are trying to achieve joint goals, or whenagents commit to achieving goals for each other. Making such a determinationfor a single goal by observing only plan traces is not trivial as agents oftendeviate from optimal plans for various reasons, including the pursuit ofmultiple goals or the inability to act optimally. In this article, we developan approach based on domain independent heuristics from automated planning,landmarks, and fact partitions to identify sub-optimal action steps - withrespect to a plan - within a plan execution trace. Such capability is veryimportant in domains where multiple agents cooperate and delegate tasks amongthemselves, e.g. through social commitments, and need to ensure that adelegating agent can infer whether or not another agent is actually progressingtowards a delegated task. We demonstrate how an agent can use our technique todetermine - by observing a trace - whether an agent is honouring a commitment.We empirically show, for a number of representative domains, that our approachinfers sub-optimal action steps with very high accuracy and detects commitmentabandonment in nearly all cases.

Using Sub-Optimal Plan Detection to Identify Commitment Abandonment in Discrete Environments