An enhancement of relational reinforcement learning

Relational reinforcement learning is a technique that combines reinforcement learning with relational learning or inductive logic programming. This technique offers greater expressive power than that one offered by traditional reinforcement learning. However, there are some problems when one wish to use it in a real time system. Most of recent research interests on incremental relational learning structure, that is a great challenge in this area. In this work, we are proposing an enhancement of TG algorithm and we illustrate the approach with a preliminary experiment. The algorithm was evaluated on a Blocks World simulator and the obtained results shown it is able to produce appropriate learn capability.