Artificial Intelligence : Foundations, Theory, and Algorithms - Eduardo Ferme

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Artificial Intelligence

Foundations, Theory, and Algorithms

By: Eduardo Ferme, Mauricio D. L. Reis, Marco Garapa

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Hardcover | 18 April 2026

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Belief change (also referred to as logic of theory change or as belief revision) is a research area that models how rational agents modify their beliefs in response to new information or experiences. It emerged as a major field of study in the mid-1980s and has since become a key topic across disciplines such as philosophy, logic, and artificial intelligence. The one that is nowadays considered the standard model of belief change is the AGM model, proposed by Alchourr³n, G¤rdenfors and Makinson in the Journal of Symbolic Logic in 1985 (the so-called AGM paper). In the four decades that have followed since, the area has developed rapidly and in many directions. The AGM model inspired many researchers to propose extensions and generalizations (for an overview see Belief Change by Ferm© and Hansson, Springer, 2018), from among which the authors highlight the models of non-prioritized belief change: These are models in which the belief change operators considered do not give priority to the new information received (contrary to what is the case regarding the AGM model which fulfils the principle of primacy of new information). For example, the output of a non-prioritized revision may not contain the new belief that has motivated that revision. Analogously, the outcome of a non-prioritized contraction may still contain the sentence by which the contraction is made. In a deep and comprehensive manner, this book summarises the contributions made to the modelling of non-prioritized belief change in the literature from 1985. All models are presented and taxonomized according to their main characteristics.

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