Computation of the Kolmogorov-Sinai entropy using statistitical   mechanics: Application of an exchange Monte Carlo method
  We propose a method for computing the Kolmogorov-Sinai (KS) entropy of chaotic systems. In this method, the KS entropy is expressed as a statistical average over the canonical ensemble for a Hamiltonian with many ground states. This Hamiltonian is constructed directly from an evolution equation that exhibits chaotic dynamics. As an example, we compute the KS entropy for a chaotic repeller by evaluating the thermodynamic entropy of a system with many ground states. 
Shin-ichi Sasa and Kumiko Hayashi