A Generalised Semantics for Belief Updates —An Equivalence-based Approach Juan C. Acosta and Jorge Hern´ andez Computer Systems UAEH-ESH, Mexico jguadarrama@gmail.com; jhcjorge@gmail.com Abstract. As suggested in the literature, revising and updating beliefs and knowledge bases is an important unsolved topic in knowledge repre- sentation and reasoning that requires a solid theoretical basis, particu- larly in current applications of Artificial Intelligence where an agent can work in an open dynamic environment with incomplete information. Var- ious researchers have combined postulates and Answer Set Programming as key components to set up their approaches. However, many of such proposals still present some shortcomings when dealing with persistence situations, redundant information, contradictions or lack of further prop- erties of knowledge evolution. In need to satisfy more general principles and suggesting a frame of reference, this paper consists of a study of con- sistency preservation and restoration, and a new AGM-characterisation of a semantics for updates of logic programs. It consists in performing updates of epistemic states that meets well-accepted belief revision postu- lates. Besides the set of properties that this framework shares with other equivalent update semantics, this proposal is also supported by a solver prototype as an important component of logic programming and auto- matic testbed of its declarative version. The existence of a solver for a theoretical framework helps to automatically compute agents’ knowledge bases for more complex prototypes and frameworks. 1 Introduction One of the goals of Artificial Intelligence and in particular of commonsense reasoning is how to make an agent intelligent that may be autonomous and capable of acting in an open dynamic environment. As suggested in the logic- programming literature, such a goal requires a solid theoretical basis on knowl- edge representation and nonmonotonic reasoning, and in particular, in knowledge updates. Logic programming is a classical well-known mechanism to code and rep- resent agents’ knowledge by means of a set of clauses called logic program. Such a program might be called a knowledge base and we code it into a semantics called Answer Sets Programming [15] or ASP in short. However, logic program- ming has typically been static in the sense that it provides no mechanism to automatically make changes (belief revision or updates) to the knowledge base. In particular, when updating knowledge one needs a way to avoid inconsis- tencies due to potential contradictory information upcoming from new evidence