Belief change based on knowledge measures

Belief Change (BC) is the process of changing beliefs (in our case, in terms of contraction, expansion and revision) taking into account a new piece of knowledge, which possibly may be in contradiction with the current belief. In this work, we present a novel quantitative BC framework based on the principle of minimizing the surprise from an information-theoretic perspective. Central to our approach is the Principle of Minimal Surprise (PMS), which asserts that when confronted with the uncertainty about which is the actual world, an agent should tend to favour the most expected, i.e., least surprising, outcomes. To formalize this, we make use of Knowledge Measures (KMs), which quantify the amount of information contained in a knowledge base. Guided by the PMS, our framework encourages belief change operations that minimize the informational amount deviation from the original belief, i.e., those that introduce the least surprise.