In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
In this paper we propose the use of small global memory for a viewer’s immediate surroundings to assist in recognising places that have been visited previously. We call this glob...
Nowadays, people start to accept fuzzy rule–based systems as flexible and convenient tools to solve a myriad of ill–defined but otherwise (for humans) straightforward tasks s...
Abstract. For time-constrained applications, repair-server-based active local recovery approaches can be valuable in providing low-latency reliable multicast service. However, an a...
The paper presents a new technique for extracting symbolic ground facts out of the sensor data stream in autonomous robots for use under hybrid control architectures, which compris...