# Comparison of two deep reinforcement learning algorithms towards an optimal policy for smart building thermal control

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/comparison-of-two-deep-reinforcement-learning-algorithms-towards-an-optimal/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Alberto Silvestri,Davide Coraci,Duan Wu,Esther Borkowski,Arno Schlueter |
| Citations | 4 |
| DOI | 10.1088/1742-6596/2600/7/072011 |
| Fields | Agricultural and Biological Sciences,Energy,Engineering |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://iopscience.iop.org/article/10.1088/1742-6596/2600/7/072011/pdf |
| OpenAlex ID | https://openalex.org/W4389223768 |
| Type | conference-paper |
| Year | 2023 |

## Paper authors

- [Alberto Silvestri](https://scholariq.org/researchers/alberto-silvestri/)

## Paper primary topic

- [Building Energy and Comfort Optimization](https://scholariq.org/topics/building-energy-and-comfort-optimization/)

## Paper topics

- [Building Energy and Comfort Optimization](https://scholariq.org/topics/building-energy-and-comfort-optimization/)
- [Energy Efficiency and Management](https://scholariq.org/topics/energy-efficiency-and-management/)
- [Greenhouse Technology and Climate Control](https://scholariq.org/topics/greenhouse-technology-and-climate-control/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.