From 29acef3cff18c00aaa9791d39d40a636a33dfd1a Mon Sep 17 00:00:00 2001
From: Christian Geishauser <christian.geishauser@hhu.de>
Date: Fri, 5 Nov 2021 12:37:20 +0000
Subject: [PATCH] Update FeudalGainPolicy.py

---
 policy/FeudalGainPolicy.py | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/policy/FeudalGainPolicy.py b/policy/FeudalGainPolicy.py
index 71236ca..88f690b 100644
--- a/policy/FeudalGainPolicy.py
+++ b/policy/FeudalGainPolicy.py
@@ -22,12 +22,15 @@
 
 
 '''
-FeudalGainPolicy.py - What Does The User Want? Information Gain for Hierarchical Dialogue Policy Optimisation
+FeudalGainPolicy.py - Information Gain for FeudalRL policies
 ==================================================
 
-Author: Christian Geishauser
+Copyright 2019-2021 HHU Dialogue Systems and Machine Learning Group
 
 The implementation of the FeudalGain algorithm that incorporates information gain as intrinsic reward in order to update a Feudal policy.
+Information gain is defined as the change in probability distributions between consecutive turns in the belief state. The distribution change is measured using the Jensen-Shannon divergence. FeudalGain builds upon the Feudal Dialogue Management architecture and optimises the information-seeking policy to maximise information gain. If the information-seeking policy for instance requests the area of a restaurant, the information gain reward is calculated by the Jensen-Shannon divergence of the value distributions for area before and after the request.
+
+
 The details can be found here: https://arxiv.org/abs/2109.07129
 
 '''
-- 
GitLab