Abstract
User supplied domain control knowledge in the form of hierarchically structured agent plans is at the heart of a number of approaches to reasoning about action. This knowledge encodes the “standard operating procedures” of an agent for responding to environmental changes, thereby enabling fast and effective action selection. This paper develops mechanisms for reasoning about a set of hierarchical plans and goals, by deriving “summary information” from the conditions on the execution of the basic actions forming the “leaves” of the hierarchy. We provide definitions of necessary and contingent pre-, in-, and postconditions of goals and plans that are consistent with the conditions of the actions forming a plan. Our definitions extend previous work with an account of both deterministic and non-deterministic actions, and with support for specifying that actions and goals within a (single) plan can execute concurrently. Based on our new definitions, we also specify requirements that are useful in scheduling the execution of steps in a set of goal-plan trees. These requirements essentially define conditions that must be protected by any scheduler that interleaves the execution of steps from different goal-plan trees.
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Notes
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We assume a procedural interpretation of goals (‘goals to do’ rather than goals to achieve a state). It is straightforward to adapt the definitions below for declarative goals.
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Note that this means the necessary conditions of an action may differ from its contingent conditions.
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For entailment, we sometimes treat a a set of literals as the conjunction of the literals in the set.
- 6.
As we are concerned with the executability of plans rather than their applicability in a particular context, we do not include the context condition (belief context) of a plan specified by a developer to be part of its precondition. However, in a well-formed plan, the necessary precondition should form (part of) the context condition of the plan.
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Plans may fail for reasons that are outside the control of the agent, e.g., due to changes in the environment, or actions of other agents violating the conditions of a plan. Several approaches, e.g., [18, 19, 21] have been proposed which attempt to avoid such failures. However, the information about goal-plan trees required by these approaches (essentially the the percentage of world states for which there is some applicable plan for any subgoal within an intention) is different from that required for scheduling, and we do not consider them further here.
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Note that if \(\rho _i\) and \(\rho _j\) are considered in order of the priority of the associated top-level goal (or ties are broken arbitrarily), deadlock (as defined in [15, 16]) cannot arise, even if there are complementary literals in \( in _n^*(\rho _j)\) and \( post _n^*(\rho _i)\). However, this may result in conditions of the lower priority set of possible execution paths being violated. In such cases, more sophisticated intention scheduling techniques, e.g., [21, 22] may be able to find an interleaving that protects the conditions of both sets of possible execution paths.
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Yao, Y., de Silva, L., Logan, B. (2016). Reasoning About the Executability of Goal-Plan Trees. In: Baldoni, M., Müller, J., Nunes, I., Zalila-Wenkstern, R. (eds) Engineering Multi-Agent Systems. EMAS 2016. Lecture Notes in Computer Science(), vol 10093. Springer, Cham. https://doi.org/10.1007/978-3-319-50983-9_10
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