Explainable and Transparent AI and Multi-Agent Systems

.- User-centric XAI.
.- Effect of Agent Explanations Using Warm and Cold Language on User Adoption of Recommendations for Bandit Problem.
.- Evaluation of the User-centric Explanation Strategies for Interactive Recommenders.
.- Can Interpretability Layouts Influence Human Perception of Offensive Sentences?.
.- A Framework for Explainable Multi-purpose Virtual Assistants: A Nutrition-Focused Case Study.
.- XAI and Reinforcement Learning.
.- Learning Temporal Task Specifications From Demonstrations.
.- Temporal Explanations for Deep Reinforcement Learning Agents.
.- An Adaptive Interpretable Safe-RL Approach for Addressing Smart Grid Supply-side Uncertainties.
.- Model-Agnostic Policy Explanations: Biased Sampling for Surrogate Models.
.- Neuro-symbolic AI and Explainable Machine Learning.
.- Explanation of Deep Learning Models via Logic Rules Enhanced by Embeddings Analysis, and Probabilistic Models.
.- py ciu image: a Python library for Explaining Image Classification with Contextual Importance and Utility.
.- Towards interactive and social explainable artificial intelligence for digital history.
.- XAI & Ethics.
.- Explainability and Transparency in Practice: A Comparison Between Corporate and National AI Ethics Guidelines in Germany and China.
.- The Wildcard XAI: from a Necessity, to a Resource, to a Dangerous Decoy.