SMC
2007
IEEE
13 years 10 months ago
2007
IEEE
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
ICMCS
2007
IEEE
13 years 10 months ago
2007
IEEE
Due to the increase in diversity of wireless devices, streaming media systems must be capable of serving multiple types of users. Scalable coding allows for adaptations without re...
ICC
2007
IEEE
13 years 10 months ago
2007
IEEE
— In this paper, we present an analytic model and methodology to determine optimal scheduling policy that involves two dimension space allocation: time and code, in High Speed Do...
CDC
2008
IEEE
13 years 10 months ago
2008
IEEE
— Consider a coverage problem for a team of agents in the plane: target points appear sporadically over time in a bounded environment and must be visited by one of the agents. It...
ALDT
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
ICC
2009
IEEE
13 years 11 months ago
2009
IEEE
—We study a sensor node with an energy harvesting source. In any slot, the sensor node is in one of two modes: Wake or Sleep. The generated energy is stored in a buffer. The sens...
ICML
2002
IEEE
14 years 5 months ago
2002
IEEE
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...