Although several researchers have integrated methods for reinforcement learning (RL) with case-based reasoning (CBR) to model continuous action spaces, existing integrations typic...
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
In reinforcement learning problems, an agent has the task of learning a good or optimal strategy from interaction with his environment. At the start of the learning task, the agent...
Tom Croonenborghs, Kurt Driessens, Maurice Bruynoo...
Modeling the cognitive processes of learners is fundamental to build educational software that are autonomous and that can provide highly tailored assistance during learning [3]. F...
Philippe Fournier-Viger, Roger Nkambou, Andr&eacut...