In this paper we propose to apply hierarchical graphs to indoor navigation. The intended purpose is to guide humans in large public buildings and assist them in wayfinding. We sta...
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...
Scientific workflows have recently emerged as a new paradigm for representing and managing complex distributed scientific computations and data analysis, and have enabled and acce...
We propose a novel approach to experience collection for autonomous service robots performing complex activities. This approach enables robots to data for many learning problems at...
A novel breadth-first based structural clustering method for graphs is proposed. Clustering is an important task for analyzing complex networks such as biological networks, World ...