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AROBOTS
1999
104views more  AROBOTS 1999»
13 years 9 months ago
Reinforcement Learning Soccer Teams with Incomplete World Models
We use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...
Marco Wiering, Rafal Salustowicz, Jürgen Schm...
IJCSA
2008
104views more  IJCSA 2008»
13 years 9 months ago
Artificial Intelligence and Bluetooth Techniques in a Multi-user M-learning Domain
In this paper we present a practical implementation of a multiuser technical laboratory that combines Artificial Intelligence (AI) and Bluetooth (BT) techniques. The objective is ...
Bonifacio Castaño, Angel Moreno, Melquiades...
NN
2007
Springer
105views Neural Networks» more  NN 2007»
13 years 9 months ago
Guiding exploration by pre-existing knowledge without modifying reward
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
Kary Främling
ICRA
2010
IEEE
215views Robotics» more  ICRA 2010»
13 years 8 months ago
Moving game theoretical patrolling strategies from theory to practice: An USARSim simulation
— Game theoretical approaches have been recently used to develop patrolling strategies for mobile robots. The idea is that the patroller and the intruder play a game, whose outco...
Francesco Amigoni, Nicola Basilico, Nicola Gatti, ...
PERCOM
2010
ACM
13 years 8 months ago
iFall - a new embedded system for the detection of unexpected falls
—This paper describes a new embedded system, called iFall, for the detection of unexpected falls for elderly people. In combination with a new sensors system and the monitoring o...
Ralf Salomon, Martin Lüder, Gerald Bieber