A combined CPG (Central Pattern Generator) based foot trajectory and GP (Genetic Programming) based joint compensation method is presented for the adaptive humanoid walking. The CPG based foot trajectory methods have been successfully applied to basic slops and variable slops with slow rates, but have a limitation for the steep slop terrains. In order to increase an adaptability of humanoid walking for the rough terrains, a GP based joint compensation method is proposed and combined to the CPG (Central Pattern Generator) based foot trajectory method. The experiments using humanoid robot Nao are conducted in an ODE based Webots simulation environmemt to verify a stability of walking for the various aslope terrains. The proposed method is compared to the previous CPG foot trajectory technique and shows better performances especially for the steep varied slopes.