We present in this paper a hybrid planning system which combines constraint satisfaction techniques and planning heuristics to produce optimal sequential plans. It integrates its ...
In this paper we describe SINERGY, which is a highly parallelizable, linear planning system that is based on the genetic programming paradigm. Rather than reasoning about the world...
The goal of assembly planning consists in generating feasible sequences to assemble a product and selecting an efficient assembly sequence from which related constraint factors su...
In this paper, a neuro-fuzzy algorithm has been implemented to improve the path planning of a mobile robot based on modification of vector field histogram (VFH) approach using neu...
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...