Search Results for author:
Found 5 papers, 1 papers with code
A Survey of Reinforcement Learning Algorithms for Dynamically Varying Environments
RL agents in these applications often need to react and adapt to changing operating conditions.
Reinforcement Learning in Non-Stationary Environments
In this paper, we thus consider the problem of developing RL methods that obtain optimal decisions in a non-stationary environment.
Memory-based Deep Reinforcement Learning for Obstacle Avoidance in UAV with Limited Environment Knowledge
When compared to obstacle avoidance in ground vehicular robots, UAV navigation brings in additional challenges because the UAV motion is no more constrained to a well-defined indoor ground or street environment.
Performance Tuning of Hadoop MapReduce: A Noisy Gradient Approach
Our method, when tested on a 25 node Hadoop cluster shows 66\% decrease in execution time of Hadoop jobs on an average, when compared to the default configuration.
Energy Sharing for Multiple Sensor Nodes with Finite Buffers
We also develop a cross entropy based method that incorporates policy parameterization in order to find near optimal energy sharing policies.
