International Journal of Geographical Information Science Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t713599799 An integrated TIN and Grid method for constructing multi-resolution digital terrain models B. Yang ab; W. Shi c; Q. Li b a GIS Divison, Department of Geography, University of Zurich-Irchel, Zuric...

Building upon prior research that highlighted the need for standardizing environments building control research, and inspired by recently introduced challenges real life reinforcement learning (RL) control, here we propose a non-exhaustive set of nine world RL in grid-interactive buildings (GIBs). We argue this area should be expressed framework addition to providing standardized environment re...

Closed-loop feedback-driven control laws can be used to solve low-thrust many-revolution trajectory design and guidance problems with minimal computational cost. Lyapunov-based offer the benefits of increased stability whilst their optimality by tuning parameters. In this paper, a reinforcement learning framework is make parameters Q-law state-dependent, increasing its optimality. The Jacobian ...

With the increasing penetration of renewable resources into low-voltage distribution grid, demand for alternatives to grid reinforcement measures has risen. One possible solution is use battery systems balance power flow at crucial locations in grid. Hereby, optimal location and size system have be determined regard investment its effect on stability. In this paper, placement sizing storage sta...

We assessed the compatibility of three Advanced Spaceborne Thermal Emission and Reflection Radometer (ASTER) based Enhanced Vegetation Index (EVI) products generated in the GEO Grid system to Moderate Resolution Imaging Spectroradiometer (MODIS) EVI. The three products were two forms of the two-band EVI with ASTER red and NIR bands but without a blue band and the original, three-band EVI comput...

Many space objects are densely distributed in the geostationary (GEO) band, and long-term impact of collision GEO spacecraft debris on environment has attracted more attention. After summarizing advantages disadvantages evolution model based “Cube” probability calculation model, “Grid” a especially suitable for was established. For four types disintegration events, used to study band after coll...

We explore the relationship between directed generative models and reinforcement learning by developing a new approach to data imputation that combines ideas from both areas. We address data imputation by defining an MDP for which we construct policies parametrized by (reasonably) large neural networks. We then show how to train these policies using a form of (self) Guided Policy Search (Levine...

This paper describes how domain knowledge of power system operators can be integrated into reinforcement learning (RL) frameworks to effectively learn agents that control the grid's topology prevent thermal cascading. Typical RL-based controllers fail perform well due large search/optimization space. Here, we propose an actor-critic-based agent address problem's combinatorial nature and train u...

We consider the policy search approach to reinforcement learning. We show that if a “baseline distribution” is given (indicating roughly how often we expect a good policy to visit each state), then we can derive a policy search algorithm that terminates in a finite number of steps, and for which we can provide non-trivial performance guarantees. We also demonstrate this algorithm on several gri...