… method for learning to refine a rule-based fuzzy logic controller. A reinforcement learning
technique is used in conjunction with a multilayer neural network model of a fuzzy controller. …

… fuzzy logic control rules and seek the optimal linguistic values of the consequences of the
fuzzy control rules in reinforcement learning… fuzzy logic control and reinforcement learning are …

… In this paper, we employ the reinforcement learning method using the Sutton and Barto’s
model [18] to fulfill this learning requirement (Fig. 5). In principle, the vehicle begins the …

… In the second scenario we use fuzzy logic and reinforcement learning jointly to train
nodes in order to estimate optimal paths. Third scenario uses sensor nodes were randomly …

… method using fuzzy logic and reinforcement learning is proposed … designed by fuzzy logic
and reinforcement learning and are … The fuzzy logic is used to represent the mapping between …

… In this paper a reinforcement learning method is used to tune the conclusion part of fuzzy …
use in this work, fuzzy controllers optimized by reinforcement learning. These controllers are …

… of fuzzy agent, which is a new paradigm for training homogeneous agents. Aiming at a lightweight
and affordable reinforcement learning … agents are conducted by fuzzy logic, which also …

… In this paper reinforcement learning and fuzzy logic approaches are used for mobile robot
navigation in unknown environment. These controllers are used for various tasks of a mobile …

… reinforcement neuralnetwork-based fuzzy logic control system (RNN-FLCS) for solving various
reinforcement learning … two neural-networkbased fuzzy logic controllers (NN-FLC’s), each …

… [a] learns and tunes a fuzzy logic controller … We first review some fundamentals of fuzzy
logic control, reinforcement learning, and credit assignment. Next, we discnss the general …