In this paper we introduce the Partition Task problem class along with a complexity measure to evaluate its instances and a performance measure to quantify the ability of a system...
Abstract. In this work, we propose a method for self-organized adaptive task partitioning in a swarm of robots. Task partitioning refers to the decomposition of a task into less co...
Marco Frison, Nam-Luc Tran, Nadir Baiboun, Arne Br...
The DAG-based task graph model has been found effective in scheduling for performance prediction and optimization of parallel applications. However the scheduling complexity and s...
Temporal partitioning techniques are useful to implement large and complex applications, which can be split into partitions in FPGA devices. In order to minimize resources, each o...
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...