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 ...
— 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...
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. ...
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...
Abstract—Overcoming the inefficiency of non-cooperative outcomes poses an important challenge for network managers in achieving efficient utilization of network resources. This...