  The worthwhile-to-move incremental principle is a mechanism where, at each
step, the agent, before moving and after exploration around the current state,
compares intermediate advantages and costs to change to advantages and costs to
stay. These advantages and costs to change include goal-setting, psychological,
cognitive, learning and inertia aspects. Acceptables moves are such that
advantages to move than to stay are higher than some fraction of costs to move
than to stay, with, as a result, a limitation of the intermediate sacrifices to
reach the goal. When the agent is more goal-oriented and improves enough at
each step, the process ends in a permanent routine, a rest point where the
agent prefers to stay than to change, in spite of some possible residual
frustration to have missed his goal. In case of high local costs to move this
approach leads to a cognitive proof of Ekeland epsilon-variational principle.
The as if hypothesis (as if agents would optimize) is revisited, leading to the
introduction of a new class of optimization algorithm with inertia, the local
search and proximal algorithms.
