Reinforcement learning algorithms that use eligibility traces, such as Sarsa(λ), have been empirically shown to be effective in learning good estimated-state-based policies in pa...
We consider the task of reinforcement learning in an environment in which rare significant events occur independently of the actions selected by the controlling agent. If these ev...
Relevance feedback (RF) is an interactive process which refines the retrievals by utilizing user’s feedback history. Most researchers strive to develop new RF techniques and ign...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...
Abstract. In [8] Yamauchi and Beer explored the abilities of continuous time recurrent neural networks (CTRNNs) to display reinforcementlearning like abilities. The investigated ta...
We present a system for visual robotic docking using an omnidirectional camera coupled with the actor critic reinforcement learning algorithm. The system enables a PeopleBot robot...