Standpoint Linear Temporal Logic
This work addresses the need for formal methods to handle temporal reasoning in scenarios with conflicting perspectives, offering a foundational extension for AI and formal verification, though it is incremental as it builds on existing logics.
The paper tackles the problem of reasoning about temporal properties in multi-agent systems with diverse viewpoints by introducing Standpoint Linear Temporal Logic (SLTL), which combines linear temporal logic with standpoint logic, and establishes its decidability, complexity, and provides a tableau calculus for automation.
Many complex scenarios require the coordination of agents possessing unique points of view and distinct semantic commitments. In response, standpoint logic (SL) was introduced in the context of knowledge integration, allowing one to reason with diverse and potentially conflicting viewpoints by means of indexed modalities. Another multi-modal logic of import is linear temporal logic (LTL) - a formalism used to express temporal properties of systems and processes, having prominence in formal methods and fields related to artificial intelligence. In this paper, we present standpoint linear temporal logic (SLTL), a new logic that combines the temporal features of LTL with the multi-perspective modelling capacity of SL. We define the logic SLTL, its syntax, and its semantics, establish its decidability and complexity, and provide a terminating tableau calculus to automate SLTL reasoning. Conveniently, this offers a clear path to extend existing LTL reasoners with practical reasoning support for temporal reasoning in multi-perspective settings.