This paper deals with the resolution of pronominal anaphora and zero anaphora in Arabic language. While researchers have treated the two phenomena separately, we propose a generic approach for both of them. Our resolution system combines a Q-learning reinforcement method and Word Embedding models. The Q-learning method uses syntactic criteria as preference factors to select candidate antecedents. It reinforces the best combination criteria for evaluating candidate antecedents. The Word Embedding models provide semantic similarity measures that help to validate the best antecedent. Our approach is evaluated on different type of Arabic texts and the obtained precision can reach79.37%.
