We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic ...
— 1In this paper, we will present a placement method for analog circuits. We consider both common centroid and 1-D symmetry constraints, which are the two most common types of pl...
In the realm of data mining, several key issues exists in the traditional classification algorithms, such as low readability, large rule number, and low accuracy with information ...
Abstract. Classic parsing methods are based on complete search techniques to find the different interpretations of a sentence. However, the size of the search space increases expon...