Valued Semantics

Valued semantics extends classical logic by assigning degrees of truth or preference to statements, moving beyond simple true/false evaluations. Current research focuses on developing and comparing different valued semantics, particularly within frameworks like linear temporal logic and answer set programming (ASP), often applied to model complex systems such as neural networks and argumentation graphs. This work aims to provide more nuanced and computationally tractable reasoning methods for handling uncertainty and defeasible knowledge, with applications in areas like artificial intelligence and knowledge representation.