Add to ORKGFuzzy logic is a mathematical approach towards the human way of thinking and learning. Based on if-then rules, we can design fuzzy controllers with the intuitive experience of human beings. However, it is not practical for a designer to find necessary number of rules and determine appropriate parameters by hand. Hence, we incorporate a reinforcement learning method with basic fuzzy rules so that the the controller can be tuned online. In this paper, we present Dynamic Fuzzy Q-Learning (DFQL).
Abstract: Programming mobile robots can be long and difficult task. The idea of having a robot learn...
This paper presents collaboration of behavior based control and fuzzy Q-learning for five legs robot...
In this paper, we discuss situations arising with reinforcement learning algorithms, when the reinfo...
Recently, the intelligent agent has become one of the important issues in Artificial Intelligence. T...
Fuzzy logic is a mathematical approach to emulate the human way of thinking. It has been shown that ...
Reinforcement Learning is the learning methodology whereby a learner develops its knowledge through ...
This paper presents a learning approach to fuzzy classifier systems. Q-learning algorithm is employe...
Abstract. In recent years, the autonomous mobile robot has found diverse applications such as home/h...
[[abstract]]This study tackles the path tracking problem of a prototype walking-aid (WAid) robot whi...
Fuzzy Q-learning is extending of Q-learning algorithm that uses fuzzy inference system to enable Q-l...
In this thesis, a novel Reinforcement Learning (RL) methodology, termed Dynamic Self-Generated Fuzz...
This paper addresses the problem of tuning the input and the output parameters of a fuzzy logic cont...
The automatic design of controllers for mobile robots usually requires two stages. In the first stag...
Abstract — This paper proposes a new fuzzy logic-based navigation method for a mobile robot moving i...
In this paper we propose a manipulated reward function for the Q-learning algorithm which is a reinf...
Abstract: Programming mobile robots can be long and difficult task. The idea of having a robot learn...
This paper presents collaboration of behavior based control and fuzzy Q-learning for five legs robot...
In this paper, we discuss situations arising with reinforcement learning algorithms, when the reinfo...
Recently, the intelligent agent has become one of the important issues in Artificial Intelligence. T...
Fuzzy logic is a mathematical approach to emulate the human way of thinking. It has been shown that ...
Reinforcement Learning is the learning methodology whereby a learner develops its knowledge through ...
This paper presents a learning approach to fuzzy classifier systems. Q-learning algorithm is employe...
Abstract. In recent years, the autonomous mobile robot has found diverse applications such as home/h...
[[abstract]]This study tackles the path tracking problem of a prototype walking-aid (WAid) robot whi...
Fuzzy Q-learning is extending of Q-learning algorithm that uses fuzzy inference system to enable Q-l...
In this thesis, a novel Reinforcement Learning (RL) methodology, termed Dynamic Self-Generated Fuzz...
This paper addresses the problem of tuning the input and the output parameters of a fuzzy logic cont...
The automatic design of controllers for mobile robots usually requires two stages. In the first stag...
Abstract — This paper proposes a new fuzzy logic-based navigation method for a mobile robot moving i...
In this paper we propose a manipulated reward function for the Q-learning algorithm which is a reinf...
Abstract: Programming mobile robots can be long and difficult task. The idea of having a robot learn...
This paper presents collaboration of behavior based control and fuzzy Q-learning for five legs robot...
In this paper, we discuss situations arising with reinforcement learning algorithms, when the reinfo...