Day-to-day replanning assumes, in a sense, ``dumb'' particles.
Particles follow routes, but the routes are pre-computed, and once the
simulation is started, they cannot be changed, for example to adapt to
unexpected congestion and/or a traffic accident. In other words, the
strategic part of the intelligence of the agents is external to the
micro-simulation. In that sense, such micro-simulations can still be
seen as, albeit much more sophisticated, version of the link cost
function 
from static assignment, now extended by influences
from other links and made dynamic throughout time. And indeed, many
dynamic traffic assignment (DTA) systems work exactly in that way
(e.g. (16)).
In terms of game theory, this means that we only allow unconditional
strategies, i.e. strategies which cannot branch during the game
depending on the circumstances.
Another way to look at this is to say that one assumes that the emergent properties of the interaction have a ``slowly varying dynamics'', meaning that one can, for example, consider congestion as relatively fixed from one day to the next. This is maybe realistic under some conditions, such as commuter traffic, but clearly not for many other conditions, such as accidents, adaptive traffic management, impulsive behavior, stochastic dynamics in general, etc. It is therefore necessary that agents are adaptive (intelligent) also on short time scales not only with respect to lane changing, but also with respect to routes and activities. It is clear that this can be done in principle, and the importance of it for fast relaxation (100,42) and for the realistic modeling of certain aspects of human behavior (3,37) has been pointed out.