  We introduce a kind of partial observability to the projective simulation
(PS) learning method. It is done by adding a belief projection operator and an
observability parameter to the original framework of the efficiency of the PS
model. I provide theoretical formulations, network representations, and
situated scenarios derived from the invasion toy problem as a starting point
for some multi-agent PS models.
