  Observing the internal state of the whole system using a small number of
sensor nodes is important in analysis of complex networks. Here, we study the
problem of determining the minimum number of sensor nodes to discriminate
attractors under the assumption that each attractor has at most K noisy nodes.
We present exact and approximation algorithms for this minimization problem.
The effectiveness of the algorithms is also demonstrated by computational
experiments using both synthetic data and realistic biological data.
