With advance of an aging society, the persons who are physically handicapped have their respective needs about mobility assist with their living conditions. Moreover, operating an electric wheelchair indoors in confined spaces requires considerable skill. This paper presents an obstacle avoiding support system for an electric wheelchair, using reinforcement learning. The obstacle avoidance is semi-automatically supported by the Minimum Vector Field Histogram (MVFH) method. The MVFH modifies the user manipulation and assists the obstacle avoidance. In the proposed scheme, the modification rate is adjusted by the reinforcement learning according to the environment and the user condition. The newly proposed scheme is numerically evaluated on a simulation example.