From f76ac4e00ef06e8e6811566c1212a13e57af56ae Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?David=20Mart=C3=ADnez?= <dmartinez@iri.upc.edu>
Date: Tue, 12 Jul 2016 14:19:29 +0000
Subject: [PATCH] ReadMe.txt edited online with Bitbucket

---
 ReadMe.txt | 29 +++++++++++++++++++++--------
 1 file changed, 21 insertions(+), 8 deletions(-)

diff --git a/ReadMe.txt b/ReadMe.txt
index 0698d65d..6c37401a 100644
--- a/ReadMe.txt
+++ b/ReadMe.txt
@@ -25,6 +25,7 @@ If you have any question or suggestion, don't hesitate to contact me:
 email: dmartinez@iri.upc.edu
 
 
+
 ===========================
 ===    Documentation    ===
 ===========================
@@ -32,15 +33,21 @@ Online documentation can be found at:
 www.iri.upc.edu/people/dmartinez/rexd_docs/index.html
 
 
+
 ======================
 ===  Introduction  ===
 ======================
-REX-D is a relational reinforcement learning with demonstrations algorithm.
+REX-D is a relational reinforcement and active learning algorithm.
 
-When using this code, please cite:
+When using this code, if using REX-D please cite:
 Relational reinforcement learning with guided demonstrations, David Martínez, 
 Guillem Alenyà, Carme Torras. Artificial Intelligence, 2016
 
+If using the domain model learner, please cite:
+Learning Relational Dynamics of Stochastic Domains for Planning, David Martínez, 
+Guillem Alenyà, Carme Torras, Tony Ribeiro and Katsumi Inoue. In proc. of the
+International Conference on Automated Planning and Scheduling, 2016, pp. 235-243
+
 
 
 ======================
@@ -121,9 +128,12 @@ Copy the learner to the bin folder
 $ cp bin/LFIT ../../bin/lfit
 
 
-======================
-===  REX-D Usage   ===
-======================
+
+==============================
+===  REX-D / V-MIN Usage   ===
+==============================
+Use RL with a teacher to solve a problem (and learn it).
+
 Go to the scenarios folder.
 $ cd scenarios
 
@@ -140,9 +150,11 @@ $ ../bin/simulator.sh
 
 
 
-======================
-=== Learner Usage  ===
-======================
+===================================
+=== Domain Model Learner Usage  ===
+===================================
+Learn a domain model from a set of input experiences.
+
 Go to the scenarios folder.
 $ cd scenarios
 
@@ -165,6 +177,7 @@ $ bin/learner_utils evaluate_rules learned_rules.ppddl 2000
 Note that the provided version of LFIT can be very slow with the Elevators domain. Our aim is to have a faster one in the short future.
 
 
+
 ======================
 ===  New domains   ===
 ======================
-- 
GitLab