In the study of symbolic reasoning, there are various formalisms to represent and model the dynamics of knowledge, among which AGM stands out, introducing belief contraction and revision operators. These operators model the basic decision-making of an agent upon receiving a new observation. When revision is applied, the agent believes in the new observation, or equivalently, disbelieves its negation. Meanwhile, contraction makes the new observation uncertain: if originally the agent consistently believed in the observation, then neither it nor its negation is believed after the contraction. Revision can thus be seen as an operator seeking certainty (either belief or disbelief), and contraction as an operator that pursues doubt (an unsettled state).
In this presentation, we introduce a new family of operators for belief change called moderated revision. This proposal aims to incorporate a feature of balance between certainty and complete doubt. We propose this as a more adequate and general model for belief change, where revision and contraction represent extreme situations. It encompasses a diverse family tree with over 20 subfamilies, including known operators, some adaptations, and novel properties. Among them, wise and imprudent operator families emerge, reflecting responses based on the strength of the new observation: wise operators tend to doubt strong affirmations, while imprudent operators tend towards unwarranted certainty.

Daniel Grimaldi holds a Licentiate degree in Mathematical Sciences from the University of Buenos Aires and is currently completing his PhD in Computer Science at the same institution under the advisor of Prof. Dr. Vanina Martinez and Prof. Dr. Ricardo Rodriguez. Over the past four years, he has been actively engaged in research with the Logic, Language, and Computability Research Group, in addition to participating in seminars with the Buenos Aires Logic Group. This interdisciplinary experience has equipped him with a versatile skill set ideal for research in Belief Change Theory and Knowledge Representation and Reasoning. He has already made contributions to the fields, with publications in IJCAI and KR conferences, as well as in the IJAR journal. Currently, he serves as a full-time teaching assistant in the Department of Computer Science and as a researcher in training in the Institute of Computer Sciences of UBA/CONICET.