Intentional Forgetting Operators—Formal Foundations and Empirical Support

Christoph Beierle (), Daniel Brand (), Diana Howey, Gabriele Kern-Isberner (), Kai Sauerwald (), Sara Todorovikj () and Marco Ragni ()
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Christoph Beierle: FernUniversität in Hagen, Faculty of Mathematics and Computer Science
Daniel Brand: TU Chemnitz, Predictive Analytics
Diana Howey: TU Dortmund University, Department of Computer Science
Gabriele Kern-Isberner: TU Dortmund University, Department of Computer Science
Kai Sauerwald: FernUniversität in Hagen, Faculty of Mathematics and Computer Science
Sara Todorovikj: TU Chemnitz, Predictive Analytics
Marco Ragni: TU Chemnitz, Predictive Analytics

A chapter in Intentional Forgetting with Intelligent Systems, 2026, pp 129-157 from Springer

Abstract: Abstract This chapter presents a framework for understanding intentional forgetting processes in humans that is jointly grounded in cognitive psychology and knowledge representation. It provides formal modeling structures, experimental designs, and best implementation practices. We identify kinds of forgetting, axiomatically formalize belief change operators involving forgetting, and elaborate their interrelationships. This general abstract framework is instantiated with conditional beliefs and realizations of forgetting operators employing ranking functions. On a cognitive level, we examine the cognitive mechanisms of intentional forgetting experimentally by employing the counting game paradigm. Our results show that changes to conditionals in procedural memory leave behind artifacts, which can improve performance when old and new conditionals align.

Date: 2026
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DOI: 10.1007/978-3-032-17621-9_7

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