Given a short query with keyphrases about a research idea in 2017 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: We propose a new control variate method to effectively reduce variance for policy gradient methods. Our method extends the

Keyphrases: reinforcement learning text

Dataset description:
Localized Narratives: We propose Localized Narratives, a new form of multimodal image annotations connecting vision and language. We ask annotators to describe an image with their voice while simultaneously hovering their mouse over the region they are describing.
SPIRS: A  first-of-its-kind large dataset of sarcastic/non-sarcastic tweets with high-quality labels and extra features: (1) sarcasm perspective labels (2) new contextual features. The dataset is expected to advance sarcasm detection research.
MuJoCo: MuJoCo (multi-joint dynamics with contact) is a physics engine used to implement environments to benchmark Reinforcement Learning methods.
CPLFW: A renovation of Labeled Faces in the Wild (LFW), the de facto standard testbed for unconstraint face verification. There are three motivations behind the construction of CPLFW benchmark as follows:  1.Establishing a relatively more difficult database to evaluate the performance of real world face verification so the effectiveness of several face verification methods can be fully justified.

Options:- A: Localized Narratives  B: SPIRS  C: MuJoCo  D: CPLFW
MuJoCo