Added polle

Author: NickCH-K

CausalInference.md

@@ -232,7 +232,12 @@ treatment effect (HTE) estimation.
     estimation of individualized treatment rules from observational and
     randomized data with options for variable-selection and gradient boosting
     based estimation, and for outcome model augmentation (for continuous,
-    binary, count, and time-to-event outcomes).
+    binary, count, and time-to-event outcomes).  `r pkg("polle")` provides a unified framework for
+    learning and evaluating finite stage policies based on observational data
+    with methods such as doubly robust restricted Q-learning, policy tree
+    learning,  and outcome weighted learning. Flexible machine learning methods
+    can be used to estimate the nuisance components and valid inference for the 
+    policy value is ensured via cross-fitting.
 -   `r pkg("OTRselect")` implements a penalized
     regression method that can simultaneously estimate the optimal
     treatment strategy and identify important variables for either