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.
To develop truly autonomous mobile robots, we propose to introduce internal rewards such as the desire for existence, specific curiosity, diversive curiosity, boredom, and novelty into reinforcement learning. They are expected to make mobile robots capable of behaving appropriately without being told what to do. Firstly, we propose to use multiple sources of rewards to endow mobile robots with ability...
This paper presents an enhanced version of the AED (Appropriate Executive Decisions) algorithm, which is based on biological immune system (BIS) and whose purpose is the generation of appropriate executive decisions aimed at business environments. A new metric has been incorporated to the algorithm and a larger and more representative database was used to train and validate results. Moreover, this...
This paper presents an application of neural network interleaved training algorithm proposed in in the domain of chess. In order to use the referenced learning method a structure of metric space is introduced in the space of chess moves. Neural network is used as a classifier of a distance from a given move to the optimal one, leading to significant limitation of the set of moves potentially worth...
Neural network is a widely used and an effective artificial intelligence technique used for predictions and classifications which has been developed based on human biological neural system. Determining the structure of a neural network is a very complex task and there is no defined approach to determine the structure, especially the number of hidden nodes. Traditionally the number of hidden nodes...
Learning classifier systems (LCSs) have gained increasing interest in the genetic and evolutionary computation literature. Many real-world problems are not conveniently expressed using the ternary representation typically used by LCSs and for such problems an interval-based representation is preferable. The new model of LCS - so-called rGCS - is used to classify real-valued data. In order to handle...
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.