This paper presents an improved approach to observation reduction in non-deterministic planning, focusing on finding the minimal observation set and the optimal observation set. The proposed method aims to reduce the complexity of observation reduction, enabling more efficient planning in complex scenarios. By leveraging advanced techniques, the approach provides a more accurate and efficient solution for observation reduction, paving the way for improved planning outcomes in various domains.