Update README.md

README.md

@@ -17,7 +17,7 @@ This repository aims to contain reliable MORL algorithms implementations in PyTo
 
 It strictly follows [MO-Gymnasium](https://github.com/Farama-Foundation/mo-gymnasium) API, which differs from the standard [Gymnasium](https://github.com/Farama-Foundation/Gymnasium) API only in that the environment returns a numpy array as the reward.
 
-For details on multi-objective MDPs (MOMDPs) and other MORL definitions, we suggest reading [A practical guide to multi-objective reinforcement learning and planning](https://link.springer.com/article/10.1007/s10458-022-09552-y).
+For details on multi-objective MDPs (MOMDPs) and other MORL definitions, we suggest reading [A practical guide to multi-objective reinforcement learning and planning](https://link.springer.com/article/10.1007/s10458-022-09552-y). An overview of some techniques used in various MORL algorithms is also provided in [Multi-Objective Reinforcement Learning Based on Decomposition: A Taxonomy and Framework](https://doi.org/10.1613/jair.1.15702).
 
 A tutorial on MO-Gymnasium and MORL-Baselines is also available: [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1ByjuUp8-CJeh1giPOACqPGiglPxDnlSq?usp=sharing)
 
@@ -47,7 +47,7 @@ A tutorial on MO-Gymnasium and MORL-Baselines is also available: [![Open in Cola
 | **Name**                                                                                                                                                             | Single/Multi-policy | ESR/SER                     | Observation space | Action space          | Paper                                                                                                                                                    |
 |----------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------|-----------------------------|-------------------|-----------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------|
 | [GPI-LS + GPI-PD](https://github.com/LucasAlegre/morl-baselines/blob/main/morl_baselines/multi_policy/gpi_pd/gpi_pd.py)                                              | Multi               | SER                         | Continuous        | Discrete / Continuous | [Paper and Supplementary Materials](https://arxiv.org/abs/2301.07784)                                                                                    |
-| [MORL/D](https://github.com/LucasAlegre/morl-baselines/blob/main/morl_baselines/multi_policy/morld/morld.py)                                                         | Multi               | /                           | /                 | /                     | [Paper](https://arxiv.org/abs/2311.12495)                                                                                                                |
+| [MORL/D](https://github.com/LucasAlegre/morl-baselines/blob/main/morl_baselines/multi_policy/morld/morld.py)                                                         | Multi               | /                           | /                 | /                     | [Paper](https://doi.org/10.1613/jair.1.15702)                                                                                                                |
 | [Envelope Q-Learning](https://github.com/LucasAlegre/morl-baselines/blob/main/morl_baselines/multi_policy/envelope/envelope.py)                                      | Multi               | SER                         | Continuous        | Discrete              | [Paper](https://arxiv.org/pdf/1908.08342.pdf)                                                                                                            |
 | [CAPQL](https://github.com/LucasAlegre/morl-baselines/blob/main/morl_baselines/multi_policy/capql/capql.py)                                                          | Multi               | SER                         | Continuous        | Continuous            | [Paper](https://openreview.net/pdf?id=TjEzIsyEsQ6)                                                                                                       |
 | [PGMORL](https://github.com/LucasAlegre/morl-baselines/blob/main/morl_baselines/multi_policy/pgmorl/pgmorl.py) <sup>[1](#f1)</sup>                                   | Multi               | SER                         | Continuous        | Continuous            | [Paper](https://people.csail.mit.edu/jiex/papers/PGMORL/paper.pdf) / [Supplementary Materials](https://people.csail.mit.edu/jiex/papers/PGMORL/supp.pdf) |