Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
It is useful for an intelligent software agent to be able to adapt to new demands from an environment. Such adaptation can be viewed as a redesign problem; an agent has some origin...
This paper is concerned with how multi-agent reinforcement learning algorithms can practically be applied to real-life problems. Recently, a new coordinated multi-agent exploratio...