— We present a new retraction algorithm for high DOF articulated models and use our algorithm to improve the performance of RRT planners in narrow passages. The retraction step i...
In this paper, we present two new run-time algorithms for the parallelization of loops that have indirect access patterns. The algorithms can handle any type of loop-carried depen...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
A linear wirelength objective more e ectively captures timing, congestion, and other global placement considerations than a squared wirelength objective. The GORDIAN-L cell placem...
Charles J. Alpert, Tony F. Chan, Dennis J.-H. Huan...
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...