  This paper examines common assumptions regarding the decision-making internal
environment for intelligent agents and investigates issues related to
processing of memory and belief states to help obtain better understanding of
the responses. In specific, we consider order effects and discuss both
classical and non-classical explanations for them. We also consider implicit
cognition and explore if certain inaccessible states may be best modeled as
quantum states. We propose that the hypothesis that quantum states are at the
basis of order effects be tested on large databases such as those related to
medical treatment and drug efficacy. A problem involving a maze network is
considered and comparisons made between classical and quantum decision
scenarios for it.
