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AAMAS
2002
Springer
14 years 9 months ago
Relational Reinforcement Learning for Agents in Worlds with Objects
In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action in a given state of the environment, so that it maximizes the total amount of reward it ...
Saso Dzeroski
IROS
2007
IEEE
176views Robotics» more  IROS 2007»
15 years 4 months ago
Handling uncertainty in semantic-knowledge based execution monitoring
— Executing plans by mobile robots, in real world environments, faces the challenging issues of uncertainty and environment dynamics. Thus, execution monitoring is needed to veri...
Abdelbaki Bouguerra, Lars Karlsson, Alessandro Saf...
ESTIMEDIA
2008
Springer
14 years 11 months ago
A stochastic approach for fine grain QoS control
We present a method for fine grain QoS control of multimedia applications. This method takes as input an application software composed of actions parameterized by quality levels. ...
Jacques Combaz, Loïc Strus
IJCAI
2001
14 years 11 months ago
An On-line Decision-Theoretic Golog Interpreter
We consider an on-line decision-theoretic interpreter and incremental execution of Golog programs. This new interpreter is intended to overcome some limitations of the off-line in...
Mikhail Soutchanski
INFOCOM
2011
IEEE
14 years 1 months ago
Incentive provision using intervention
Abstract—Overcoming the inefficiency of non-cooperative outcomes poses an important challenge for network managers in achieving efficient utilization of network resources. This...
Jaeok Park, Mihaela van der Schaar