While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
— Single-query sampling-based motion planners are an efficient class of algorithms widely used today to solve challenging motion planning problems. This paper exposes the common...
The complexity and dynamic nature of travelling offers many opportunities for technological support. But printed guidebooks remain the typical companion, despite many weaknesses. ...
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 August of 1998 I completed the first hypertextual dissertation at Rensselaer Polytechnic Institute. The dissertation was a case study applying methods of rhetorical analysis an...