Iterated Belief Change, Computationally
This addresses foundational issues in AI and logic for researchers in belief dynamics, but it is incremental as it builds on existing principles.
The paper tackled the problem of connecting iterated belief change to computation, showing that iterative belief revision is Turing complete even under established principles like the Darwiche-Pearl postulates.
Iterated Belief Change is the research area that investigates principles for the dynamics of beliefs over (possibly unlimited) many subsequent belief changes. In this paper, we demonstrate how iterated belief change is connected to computation. In particular, we show that iterative belief revision is Turing complete, even under the condition that broadly accepted principles like the Darwiche-Pearl postulates for iterated revision hold.