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Grid cluster resource scheduling is a NP problem, the given grid cluster resource scheduling method has the long scheduling time and unbalance system load, a cooperative dependent task scheduling method based on reinforcement learning and parallel ant colony algorithm is proposed. Firstly, the scheduling goal model based on DAG model is defined, then the improved one step TD algorithm such as Q-learning is used to allocate the task resource, and saving the Q value of scheduling schema. Then an improved ant colony algorithm is introduce to realize the allocation of task to the resource node. The Q value obtained from the Q-learning algorithm is used to initialize the pheromone of the route to avoid the search of the ant in ant colony. The Q value is also considered into the probability function to make it has the heuristic ability. The experiment is operated in the Gridsim environment, the result shows the method in this paper can realize the cooperative dependent task cluster scheduling, and compared with the other methods, it has the less task scheduling time and high load balance level, therefore, it is a feasible scheduling method suitable for grid environment with big priority.