We present a centralized and a distributed algorithms for scheduling multi-task agents in heterogeneous networks. Our centralized algorithm has an upper bound on the overall compl...
Abstract--We consider the problem of delay-efficient scheduling in general multihop networks. While the class of max-weight type algorithms are known to be throughput optimal for t...
We study the preemptive scheduling problem of a set of n jobs with release times and equal processing times on a single machine. The objective is to minimize the sum of the weighte...
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Efficient task scheduling is critical to achieving high performance on grid computing environment. A heuristic task scheduling algorithm satisfied resources load balancing on grid ...