@@ -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 . 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:
A-MFEA-RL depends on Metaworld and (license required). To install Metaworld please follow the instructions in the  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:
