![]() ![]() Online and Compositional Learning ofControllers with Application Empowered with efficient techniques and tools, game 1 One novel approach which is being developed and applied in the on-going EU FP7 project CASSTING 1 is that of game theory. The connectivity in the home enables new, intelligent and personalized con- trol strategies for (and across) activities in the house. In particular, several devices may be connected through a home network to allow control by a personal computer, and may allow remote access from the internet. ![]() Also the emergence of “Internet of Things” has tied in closely with the popularization of home automation. The popularity of home automation has increased significantly in recent years through affordable smartphone and tablet connectivity. The overall goal is to achieve improved convenience, comfort, energy efficiency as well as security. 1 Introduction Home automation includes the centralized control of a number of functionalities in a house such as lighting, HVAC (heating, ventilation and air conditioning), appliances, security locks of gates and doors as well as other systems. Finally, we demonstrate the applicability of the methodology to a concrete floor heating system of a real family house. For additional scalability we propose and apply a compositional synthesis approach. This computation is itself done by employing machine learning in order to avoid enumeration of the whole state-space. Instead of off-line synthesis of a controller for all possible input temperatures and an arbi- trary time horizon, we propose an on-line synthesis methodology, where we periodically compute the controller only for the near future based on the current sensor readings. We suggest a general and scalable methodology for controller synthesis for such systems. temperature readings in the different rooms) and even after digitization, the state-space remains huge and cannot be fully explored. The state-space to be explored is in general uncountable due to the presence of continuous variables (e.g. a floor heating system in a house, is a complex computational task that cannot be solved by an exhaustive search though all the con- trol options. Controller synthesis for stochastic hybrid switched systems, like e.g. Larsen, Marius Mikuˇ cionis, Marco Mu˜ niz, Jiˇ r´ ı Srba, and Jakob Haahr Taankvist Department of Computer Science, Aalborg University, Denmark Abstract. Save your configurations and load them whenever you want to start a game.Online and Compositional Learning of Controllers with Application to Floor Heating Kim G.Play games in classic mode, 40 vs 40, or in fast mode, 16 vs 16.Challenge your friends or randomly selected players.The goal is to capture the enemy's flag before they can take yours. As you may know, you have soldiers of different ranks as well as bombs to blow up anyone who targets you. You arrange your soldiers on the battlefield (you can save that configuration or load others) and you face your rival. This is a multiplayer version where you can fight randomly chosen users from all over the world or against your own friends. As you may know, it is based on a military ranking system: two pieces face each other and the one with the highest rank wins. In Stratego, one of the most famous board games of all time, you simulate a battle on the tabletop with military units similar to those of the European forces from the 19th century. ![]()
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