This paper combines fuzzy inference algorithm with the simulated annealing modified Q (λ) learning algorithm to solve the problem of robot who avoids obstacles in unknown environments. The system learns autonomously by itself without supervision or any prior training data. One of the popular methods for path planning algorithm is improved simulated annealing Q (λ)-learning. The fuzzy logic control is utilized to solve the generalization of continuous space. The combination of the two algorithms can solve the generalization of the continuous state space. Another advantage is that it can reach the balance of the exploration and utilization of the action strategy. The Simulation results exhibit the effectiveness of the proposed method compared with the original method.
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