The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper we establish a general social intelligent algorithmic framework for packing problem under the help of the conception of social computing. In this framework, packing problem can be solved intelligently, with the same asymptotic bounds by applying the existing packing algorithms. More precisely, our framework is designed to intelligently adopt the most proper one among all the given existing...
In many applications, data does not take the form of traditional stored relations, but rather arrives in continuous, rapid, time-varying data streams,and data streams are potentially unbounded in size. Focusing on the problem of sampling from landmark windows over data streams, a new concept, which is called stratified sampling ratio function, is presented. Then a multistage stratified sampling algorithm...
A new reactive behavior design algorithm is introduced. It is achieved through deliberative behavior learning. The deliberative behavior is a static local optimal path planning, which is learned by Q-learning (QL) method of the reinforcement learning (RL). Control rules are formed after learning and are acted as a reflection of the implementation. A lookup-Q matrix McircQ which size is 11times192...
A new obstacle avoidance algorithm for the mobile robot is introduced. When the dynamic obstacle is in a nonlinear random movement, a radial basis function neural network (RBFNN) is used to build the prediction model. The next location of the obstacle is predicted based on the three adjacent value of time sequence. Thus the dynamic obstacle avoidance issue is converted into the instantaneous static...
A new global path planning method the steepest descend method (SDM), which is suitable to the grid map, is introduced according to the global path planning. It uses the principle of the shortest line between two points as the heuristic information to propagates distances through free cells from the start cell and forms a different gradient around it. With the idea of the first search greed best, the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.