2019
AAAI
AAAI 2019
Verification of RNN-Based Neural Agent-Environment Systems
Abstract
Abstract We introduce agent-environment systems where the agent is stateful and executing a ReLU recurrent neural network. We define and study their verification problem by providing equivalences of recurrent and feed-forward neural networks on bounded execution traces. We give a sound and complete procedure for their verification against properties specified in a simplified version of LTL on bounded executions. We present an implementation and discuss the experimental results obtained.
🚀
Conference Pioneer
— AAAI 2019
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Knowledge & Reasoning and Machine Learning
🧭
Keyword Pioneer
— agent-environment system
🐣
Hot Topic Early Bird
— formal verification
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Topics
Artificial Intelligence > Core AI > Agent Systems
Artificial Intelligence > Core AI > AI Safety
Artificial Intelligence > Core AI > Interpretability
Machine Learning > Optimization & Theory > Theory
Deep Learning > Architectures > Neural Networks
Knowledge & Reasoning > Reasoning > Formal Methods
Machine Learning > Core Methods > Interpretability