This paper presents an introduction to reinforcement learning and relational reinforcement learning at a level to be understood by students and researchers with different backgrounds. It gives an overview of the fundamental principles and techniques of reinforcement learning without involving a rigorous deduction of the mathematics involved through the use of an example application. Then, relational reinforcement learning is presented as a combination of reinforcement learning with relational learning. Its advantages — such as the possibility of using structural representations, making abstraction from specific goals pursued and exploiting the results of previous learning phases — are discussed.status: publishe
Humans perceive the world in terms of objects and relations between them. In fact, for any given pai...
Relational reinforcement learning is a promising direction within reinforcement learning research. I...
In this paper we present a new method for reinforcement learning in relational domains. A logical la...
This paper presents an introduction to reinforcement learning and relational reinforcement learning ...
Relational Reinforcement Learning (RRL) is both a young and an old field. In this paper, we trace th...
Reinforcement learning has developed into a primary approach for learning control strategies for aut...
Reinforcement learning has developed into a primary approach for learning control strategies for aut...
Abstract. In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action...
Relational reinforcement learning has allowed results from reinforcement learning tasks to be re-use...
We present a perspective and challenges for Relational Reinforcement Learning (RRL). We first survey...
In recent years, there has been a growing interest in using rich representations such as relational ...
In recent years, there has been a growing interest in using rich representations such as relational...
Relational reinforcement learning is a promising new direction within reinforcement learning researc...
Relational Reinforcement Learning (RRL) is both a young and an old eld. In this pa-per, we trace the...
Transfer learning is an inherent aspect of human learning. When humans learn to perform a task, we r...
Humans perceive the world in terms of objects and relations between them. In fact, for any given pai...
Relational reinforcement learning is a promising direction within reinforcement learning research. I...
In this paper we present a new method for reinforcement learning in relational domains. A logical la...
This paper presents an introduction to reinforcement learning and relational reinforcement learning ...
Relational Reinforcement Learning (RRL) is both a young and an old field. In this paper, we trace th...
Reinforcement learning has developed into a primary approach for learning control strategies for aut...
Reinforcement learning has developed into a primary approach for learning control strategies for aut...
Abstract. In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action...
Relational reinforcement learning has allowed results from reinforcement learning tasks to be re-use...
We present a perspective and challenges for Relational Reinforcement Learning (RRL). We first survey...
In recent years, there has been a growing interest in using rich representations such as relational ...
In recent years, there has been a growing interest in using rich representations such as relational...
Relational reinforcement learning is a promising new direction within reinforcement learning researc...
Relational Reinforcement Learning (RRL) is both a young and an old eld. In this pa-per, we trace the...
Transfer learning is an inherent aspect of human learning. When humans learn to perform a task, we r...
Humans perceive the world in terms of objects and relations between them. In fact, for any given pai...
Relational reinforcement learning is a promising direction within reinforcement learning research. I...
In this paper we present a new method for reinforcement learning in relational domains. A logical la...