—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
: Independent, heterogeneous, distributed, sometimes transient and mobile data sources produce an enormous amount of information that should be semantically integrated and filtere...
Higher level semantics are considered useful in the geospatial domain, yet there is no general consensus on the form these semantics should take. Indeed, knowledge representation p...
Abstract. Analysing human behavior is a key step in smart home applications. Many reasoning approaches utilize information of location and posture of the occupant in qualitative as...
In this paper we describe the development of an ontology of molecular and phenotypic cereals data, realized by integrating existing public web databases with the database developed...