Explainability in deep reinforcement learning

A Heuillet, F Couthouis, N Díaz-Rodríguez - Knowledge-Based Systems, 2021 - Elsevier
A large set of the explainable Artificial Intelligence (XAI) literature is emerging on feature
relevance techniques to explain a deep neural network (DNN) output or explaining models …

Explainable reinforcement learning: A survey

E Puiutta, EMSP Veith - … cross-domain conference for machine learning …, 2020 - Springer
Abstract Explainable Artificial Intelligence (XAI), ie, the development of more transparent and
interpretable AI models, has gained increased traction over the last few years. This is due to …

Explaining Deep Reinforcement Learning-Based Methods for Control of Building HVAC Systems

J Jiménez-Raboso, A Manjavacas… - World Conference on …, 2023 - Springer
Deep reinforcement learning (DRL) has emerged as a powerful tool for controlling complex
systems, by combining deep neural networks with reinforcement learning techniques …

[PDF][PDF] Explaining Deep Reinforcement Learning-based methods for control of building HVAC systems

J Gómez-Romero - methods - researchgate.net
Deep reinforcement learning (DRL) has emerged as a powerful tool for controlling complex
systems, by combining deep neural networks with reinforcement learning techniques …

Building Human-Autonomy Teaming Aids for Real-Time Strategy Games

C Izumigawa, C Lucero, L Nans, K Frederiksen… - … 2020, Held as Part of the …, 2020 - Springer
StarCraft II (SC2) is a real-time strategy science-fiction video game developed by Blizzard
Entertainment. Known for its complex state space and open-source environment [8], SC2 …