Event-driven temporal models for explanations - ETeMoX: explaining reinforcement learning

Grand challenges in model-driven engineering: an analysis of the state of the research

(2020) Antonio Bucchiarone et al.   Software and Systems Modeling

Interestingness Elements for Explainable Reinforcement Learning: Understanding Agents' Capabilities and Limitations

(2020) Pedro Sequeira et al.   ARTIFICIAL INTELLIGENCE

A stream processing architecture for heterogeneous data sources in the Internet of Things

(2020) David Corral-Plaza et al.   COMPUTER STANDARDS & INTERFACES

Integrating complex event processing and machine learning: An intelligent architecture for detecting IoT security attacks

(2020) José Roldán et al.   EXPERT SYSTEMS WITH APPLICATIONS

Explainability in deep reinforcement learning

(2020) Alexandre Heuillet et al.   KNOWLEDGE-BASED SYSTEMS

Models@run.time: a guided tour of the state of the art and research challenges

(2019) Nelly Bencomo et al.   Software and Systems Modeling

A Sentinel Node for Event-Driven Structural Monitoring of Road Bridges Using Wireless Sensor Networks

(2019) Glauco Feltrin et al.   Journal of Sensors

ChronoSphere: a graph-based EMF model repository for IT landscape models

(2019) Martin Haeusler et al.   Software and Systems Modeling

Applications of Deep Learning and Reinforcement Learning to Biological Data

(2018) Mufti Mahmud et al.   IEEE Transactions on Neural Networks and Learning Systems

Integrating Models of Interval Timing and Reinforcement Learning

(2018) Elijah A. Petter et al.   TRENDS IN COGNITIVE SCIENCES

Peeking inside the black-box: A survey on Explainable Artificial Intelligence (XAI)

(2018) Amina Adadi et al.   IEEE Access

Artificial intelligence, machine learning and health systems

(2018) Trishan Panch et al.   Journal of Global Health

Automated risk identification using NLP in cloud based development environments

(2017) K. Vijayakumar et al.   Journal of Ambient Intelligence and Humanized Computing

Wireless communications with unmanned aerial vehicles: opportunities and challenges

(2016) Yong Zeng et al.   IEEE COMMUNICATIONS MAGAZINE

Can we open the black box of AI?

(2016) Davide Castelvecchi   NATURE

Event-driven strain cycle monitoring of railway bridges using a wireless sensor network with sentinel nodes

(2016) Nemanja Popovic et al.   Structural Control & Health Monitoring

Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model

(2015) Benjamin Letham et al.   Annals of Applied Statistics

MEdit4CEP: A model-driven solution for real-time decision making in SOA 2.0

(2015) Juan Boubeta-Puig et al.   KNOWLEDGE-BASED SYSTEMS

Human-level control through deep reinforcement learning

(2015) Volodymyr Mnih et al.   NATURE

Models@ run.time

(2009) Gordon Blair et al.   COMPUTER