tdpeuter/2026SEL3-project-Brittle_Star_Controller_Modularity
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@ -17,7 +17,7 @@ failures.
Alternative learning algorithms include:
- **Twin Delayed DDPG (Fujimoto et al., 2018)**: TD3 is a strong off-policy alternative used in the SMP paper (Huang et
al., 2020). It is highly sample-efficient and reportedly excels at zero-shot adaptions. However, this approach would be
al., 2020). It is highly sample-efficient and reportedly excels at zero-shot adaptations. However, this approach would be
more complex and error-prone than with PPO.
- **Evolution strategies (ES)**: Evolution strategies are useful for optimizing Central Pattern Generators (CPGs), e.g.
CMA-ES, OpenAI-ES. While this method is easier to distribute and parallelize, ES typically scales worse with
@ -25,6 +25,6 @@ exceptionally large observation spaces compared to gradient-based RL methods lik
**References**
- Fujimoto, Scott, Herke Hoof, en David Meger. ‘Addressing Function Approximation Error in Actor-Critic Methods’. Proceedings of the 35th International Conference on Machine Learning, 3 juli 2018, 1587-96. https://proceedings.mlr.press/v80/fujimoto18a.html.
- Huang, Wenlong, Igor Mordatch, en Deepak Pathak. ‘One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control’. arXiv:2007.04976. Preprint, arXiv, 9 juli 2020. https://doi.org/10.48550/arXiv.2007.04976.
- Schulman, John, Filip Wolski, Prafulla Dhariwal, Alec Radford, en Oleg Klimov. ‘Proximal Policy Optimization Algorithms’. arXiv:1707.06347. Preprint, arXiv, 28 augustus 2017. https://doi.org/10.48550/arXiv.1707.06347.
- Fujimoto, Scott, Herke Hoof, and David Meger. ‘Addressing Function Approximation Error in Actor-Critic Methods’. Proceedings of the 35th International Conference on Machine Learning, 3 July 2018, 1587-96. https://proceedings.mlr.press/v80/fujimoto18a.html.
- Huang, Wenlong, Igor Mordatch, and Deepak Pathak. ‘One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control’. arXiv:2007.04976. Preprint, arXiv, 9 July 2020. https://doi.org/10.48550/arXiv.2007.04976.
- Schulman, John, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. ‘Proximal Policy Optimization Algorithms’. arXiv:1707.06347. Preprint, arXiv, 28 August 2017. https://doi.org/10.48550/arXiv.1707.06347.