Explainable reinforcement learning: A survey and comparative review
Explainable reinforcement learning (XRL) is an emerging subfield of explainable machine
learning that has attracted considerable attention in recent years. The goal of XRL is to …
learning that has attracted considerable attention in recent years. The goal of XRL is to …
A survey on artificial intelligence assurance
Artificial Intelligence (AI) algorithms are increasingly providing decision making and
operational support across multiple domains. AI includes a wide (and growing) library of …
operational support across multiple domains. AI includes a wide (and growing) library of …
A survey of explainable reinforcement learning
Explainability in deep reinforcement learning: A review into current methods and applications
T Hickling, A Zenati, N Aouf, P Spencer - ACM Computing Surveys, 2023 - dl.acm.org
The use of Deep Reinforcement Learning (DRL) schemes has increased dramatically since
their first introduction in 2015. Though uses in many different applications are being found …
their first introduction in 2015. Though uses in many different applications are being found …
Concept learning for interpretable multi-agent reinforcement learning
Multi-agent robotic systems are increasingly operating in real-world environments in close
proximity to humans, yet are largely controlled by policy models with inscrutable deep neural …
proximity to humans, yet are largely controlled by policy models with inscrutable deep neural …
[HTML][HTML] Explainable generative design in manufacturing for reinforcement learning based factory layout planning
Generative design can be an effective approach to generate optimized factory layouts. One
evolving topic in this field is the use of reinforcement learning (RL)-based approaches …
evolving topic in this field is the use of reinforcement learning (RL)-based approaches …
A conceptual framework for externally-influenced agents: An assisted reinforcement learning review
A long-term goal of reinforcement learning agents is to be able to perform tasks in complex
real-world scenarios. The use of external information is one way of scaling agents to more …
real-world scenarios. The use of external information is one way of scaling agents to more …
An evaluation methodology for interactive reinforcement learning with simulated users
Interactive reinforcement learning methods utilise an external information source to evaluate
decisions and accelerate learning. Previous work has shown that human advice could …
decisions and accelerate learning. Previous work has shown that human advice could …