In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action in a given state of the environment, so that it maximizes the total amount of reward it ...
The identification of bronchovascular pairs on High Resolution Computer Tomography (HRCT) images provides valuable diagnostic information in patients with suspected airway disease...
Abstract. Imitative learning can be considered an essential task of humans development. People use instructions and demonstrations provided by other human experts to acquire knowle...
Grazia Bombini, Nicola Di Mauro, Teresa Maria Alto...
This paper develops a new paradigm for relational learning which allows for the representation and learning of relational information using propositional means. This paradigm sugg...