  Decision makers involved in the management of civil assets and systems
usually take actions under constraints imposed by societal regulations. Some of
these constraints are related to epistemic quantities, as the probability of
failure events and the corresponding risks. Sensors and inspectors can provide
useful information supporting the control process (e.g. the maintenance process
of an asset), and decisions about collecting this information should rely on an
analysis of its cost and value. When societal regulations encode an economic
perspective that is not aligned with that of the decision makers, the Value of
Information (VoI) can be negative (i.e., information sometimes hurts), and
almost irrelevant information can even have a significant value (either
positive or negative), for agents acting under these epistemic constraints. We
refer to these phenomena as Information Avoidance (IA) and Information
OverValuation (IOV). In this paper, we illustrate how to assess VoI in
sequential decision making under epistemic constraints (as those imposed by
societal regulations), by modeling a Partially Observable Markov Decision
Processes (POMDP) and evaluating non optimal policies via Finite State
Controllers (FSCs). We focus on the value of collecting information at current
time, and on that of collecting sequential information, we illustrate how these
values are related and we discuss how IA and IOV can occur in those settings.
