This paper describes a domain description language DDL.1 able to represent physical domains to solve planning and scheduling problems. DDL.1 uses a representation, inspired by classical control theory, based on state-variables to represent the relevant features of a domain. Each state variable is meant to represent a set of plausible temporal evolutions those features may have. DDL.1 allows to ...

D-alanine: D-alanine ligase (DDL) is a vital enzyme in the bacterial cell wall biosynthesis. It is involved in the synthesis of D-alanine dipeptide which crosslinks the peptidoglycan for integrity. In this study, the 3Dimensional structure of theDDL of Enterococcus faecalis (E.faecalis) was determined through Homology Modeling, on the basis of crystal structure coordinates of DDL of Staphylococ...

The last decade of basic research in the area of Description Logics (DL) has created a stable theory, efficient inference procedures, and has demonstrated a wide applicability of DL to knowledge representation and reasoning. The success of DL in the semantic web and the distributed nature of the last one inspired recently a proposal of Distributed DL framework (DDL). DDL is composed of a set of...

The dynamic description logic DDL provides a kind of action theories based on description logics (DLs). Compared with another important DL-based action formalism constructed by Baader et.al., a shortcoming of DDL is the absence of occlusions and conditional postconditions in the description of atomic actions. In this paper, we extend atomic action definitions of DDL to overcome this limitation....

Effective utilization of cache memories is a key factor in achieving high performance in computing the Discrete Fourier Transform (DFT). Most optimization techniques for computing the DFT rely on either modifying the computation and data access order or exploiting low level platform specific details, while keeping the data layout in memory static. In this paper, we propose a high level optimiza...

This paper presents a novel framework for Offline Reinforcement Learning (RL) with online fine tuning Heating Ventilation and Air-conditioning (HVAC) systems. The method to do pre-training in black box model environment, where the models are built on data acquired under traditional control policy. focuses application of Underfloor (UFH) an air-to-water-based heat pump. However, should also gene...