  Many studies on animal and human movement patterns report the existence of
scaling laws and power-law distributions. Whereas a number of random walk
models have been proposed to explain observations, in many situations
individuals actually rely on mental maps to explore strongly heterogeneous
environments. In this work we study a model of a deterministic walker, visiting
sites randomly distributed on the plane and with varying weight or
attractiveness. At each step, the walker minimizes a function that depends on
the distance to the next unvisited target (cost) and on the weight of that
target (gain). If the target weight distribution is a power-law, $p(k)\sim
k^{-\beta}$, in some range of the exponent $\beta$, the foraging medium induces
movements that are similar to L\'evy flights and are characterized by
non-trivial exponents. We explore variations of the choice rule in order to
test the robustness of the model and argue that the addition of noise has a
limited impact on the dynamics in strongly disordered media.
