Reasoning about actions with EL ontologies with temporal answer sets
This work addresses the integration of ontological reasoning with action theories for AI planning and knowledge representation, but it appears incremental as it builds on existing temporal answer set frameworks.
The paper tackles the problem of reasoning about actions with ontological knowledge by proposing an approach based on Answer Set Programming, using temporal answer sets to handle non-deterministic actions and causal rules, and provides conditions for action consistency with respect to an EL^⊥ ontology through a polynomial encoding.
We propose an approach based on Answer Set Programming for reasoning about actions with domain descriptions including ontological knowledge, expressed in the lightweight description logic EL^\bot. We consider a temporal action theory, which allows for non-deterministic actions and causal rules to deal with ramifications, and whose extensions are defined by temporal answer sets. We provide conditions under which action consistency can be guaranteed with respect to an ontology, by a polynomial encoding of an action theory extended with an EL^\bot knowledge base (in normal form) into a temporal action theory.