GROWTH OF SOCIAL NETWORK ANALYSIS AS AN ACADEMIC FIELD HAS COINCIDED WITH AN EXPLOSION IN POPULAR INTEREST IN SOCIAL NETWORKS. EXPERT FINDING IS ONE OF THE MOST IMPORTANT SUBJECTS FOR MINING FROM SOCIAL NETWORKS SEARCHING FOR THE RIGHT PERSONS WITH THE APPROPRIATE SKILLS AND KNOWLEDGE. THE RLS ALGORITHM EXPLOITED Q-LEARNING AND REFERRALS TO FIND EXPERTS IN SOCIAL NETWORK TO SEARCH EXPERT IN SOCIAL NETWORK. COMPARISON OF RLS WITH SIMPLE SEARCH ALGORITHM, REFERRAL ALGORITHM AND SNPAGERANK SHOWS INCREASE IN BOTH PRECISION AND RECALL. RLS LEARNS TO FIND NEW EXPERTS AS OLD EXPERTS SUBSTITUTE THEIR ROLE WITH NEW ONES DUE TO CHANGES IN SOCIAL NETWORK ENVIRONMENT.