diff --git a/README.md b/README.md
index a26388ad9646bff6e619077a350522ff25c7b7db..f0fee497b9d0935bea3d2ba2f92b3bc62f466142 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,7 @@ In the framework, a reformulation of the well-known MFEA/MFEA-II algorithms is i
 2. **Adapted crossover operator**: the crossover operator must support the previous aspects by preventing neural models from exchanging irrelevant information.
 3. **Layer-based Transfer Learning**: unlike in traditional means to implement Transfer Learning, the number of layers to be transferred between models evolved for different tasks is autonomously decided by A-MFEA-RL during the search. 
 
-The code works on top of ![Metaworld-v1](https://github.com/rlworkgroup/metaworld). The experimentation carried out considers three scenarios; *TOY*, *MT-10/MT-10-R* and *MT-50/MT-50-R* (Results included in [Results](#results) Section ), *R* denotes random initialized episodes as in the next image: 
+The code works on top of [Metaworld-v1](https://github.com/rlworkgroup/metaworld). The experimentation carried out considers three scenarios; *TOY*, *MT-10/MT-10-R* and *MT-50/MT-50-R* (Results included in [Results](#results) Section ), *R* denotes random initialized episodes as in the next image: 
 
 <h3>MT-10-R results
 <img src="/uploads/c743460c60cddf1bb099ecae3ea6365d/MT10.gif" width="80%" /> </h3>
@@ -23,7 +23,7 @@ conda env create -f mujoco36.yml
 conda activate mujoco36
 ```
 
-A-MFEA-RL depends on Metaworld and ![MuJoco](https://github.com/openai/mujoco-py) (license required). To install Metaworld please follow the instructions in the ![official GitHub](https://github.com/rlworkgroup/metaworld) or run:
+A-MFEA-RL depends on Metaworld and [MuJoco](https://github.com/openai/mujoco-py) (license required). To install Metaworld please follow the instructions in the [official GitHub](https://github.com/rlworkgroup/metaworld) or run:
 
 ```bash
 pip install git+https://github.com/rlworkgroup/metaworld.git@master#egg=metaworld