:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gross, Dennis, Spieker, Helge
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence
Online Access:	https://arxiv.org/abs/2403.18725
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Co-Activation Graph Analysis of Safety-Verified and Explainable Deep Reinforcement Learning Policies
by: Gross, Dennis, et al.
Published: (2025)

Bounded PCTL Model Checking of Large Language Model Outputs
by: Gross, Dennis, et al.
Published: (2025)

Verifying Memoryless Sequential Decision-making of Large Language Models
by: Gross, Dennis, et al.
Published: (2025)

Safety-Oriented Pruning and Interpretation of Reinforcement Learning Policies
by: Gross, Dennis, et al.
Published: (2024)

Translating the Rashomon Effect to Sequential Decision-Making Tasks
by: Gross, Dennis, et al.
Published: (2025)

Turn-based Multi-Agent Reinforcement Learning Model Checking
by: Gross, Dennis
Published: (2025)

Enhancing Manufacturing Quality Prediction Models through the Integration of Explainability Methods
by: Gross, Dennis, et al.
Published: (2024)

Semi-supervised CAPP Transformer Learning via Pseudo-labeling
by: Gross, Dennis, et al.
Published: (2026)

Formal Verification of Noisy Quantum Reinforcement Learning Policies
by: Gross, Dennis
Published: (2025)

Enhancing RL Safety with Counterfactual LLM Reasoning
by: Gross, Dennis, et al.
Published: (2024)

Formally Verifying and Explaining Sepsis Treatment Policies with COOL-MC
by: Gross, Dennis
Published: (2026)

COOL-MC: Verifying and Explaining RL Policies for Platelet Inventory Management
by: Gross, Dennis
Published: (2026)

Constrained and Robust Policy Synthesis with Satisfiability-Modulo-Probabilistic-Model-Checking
by: Heck, Linus, et al.
Published: (2025)

COOL-MC: Verifying and Explaining RL Policies for Multi-bridge Network Maintenance
by: Gross, Dennis
Published: (2026)

Towards Trustworthy Automated Driving through Qualitative Scene Understanding and Explanations
by: Belmecheri, Nassim, et al.
Published: (2024)

Evaluating Human Trajectory Prediction with Metamorphic Testing
by: Spieker, Helge, et al.
Published: (2024)

Trustworthy Automated Driving through Qualitative Scene Understanding and Explanations
by: Belmecheri, Nassim, et al.
Published: (2024)

Explainable Scene Understanding with Qualitative Representations and Graph Neural Networks
by: Belmecheri, Nassim, et al.
Published: (2025)

Prompting for Performance: Exploring LLMs for Configuring Software
by: Spieker, Helge, et al.
Published: (2025)

Reusable Test Suites for Reinforcement Learning
by: Betten, Jørn Eirik, et al.
Published: (2025)

Rashomon in the Streets: Explanation Ambiguity in Scene Understanding
by: Spieker, Helge, et al.
Published: (2025)

Fact-Checking with Large Language Models via Probabilistic Certainty and Consistency
by: Wang, Haoran, et al.
Published: (2026)

Robust Probabilistic Model Checking with Continuous Reward Domains
by: Ji, Xiaotong, et al.
Published: (2025)

Probabilistic Satisfaction of Temporal Logic Constraints in Reinforcement Learning via Adaptive Policy-Switching
by: Lin, Xiaoshan, et al.
Published: (2024)

Probabilistic Shielding for Safe Reinforcement Learning
by: Court, Edwin Hamel-De le, et al.
Published: (2025)

ProSh: Probabilistic Shielding for Model-free Reinforcement Learning
by: Court, Edwin Hamel-De le, et al.
Published: (2025)

Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment
by: Han, Gengyue, et al.
Published: (2026)

ISEP: Implicit Support Expansion for Offline Reinforcement Learning via Stochastic Policy Optimization
by: Chen, Yifei, et al.
Published: (2026)

Stochastic Diffusion: A Diffusion Probabilistic Model for Stochastic Time Series Forecasting
by: Liu, Yuansan, et al.
Published: (2024)

Probabilistic Curriculum Learning for Goal-Based Reinforcement Learning
by: Salt, Llewyn, et al.
Published: (2025)

Efficient Reinforcement Learning in Probabilistic Reward Machines
by: Lin, Xiaofeng, et al.
Published: (2024)

Probabilistic Constraint for Safety-Critical Reinforcement Learning
by: Chen, Weiqin, et al.
Published: (2023)

Neuronal Stochastic Attention Circuit (NSAC) for Probabilistic Representation Learning
by: Razzaq, Waleed, et al.
Published: (2026)

Checking Trustworthiness of Probabilistic Computations in a Typed Natural Deduction System
by: D'Asaro, Fabio Aurelio, et al.
Published: (2022)

Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning
by: Schnitzer, Yannik, et al.
Published: (2026)

Robust Probabilistic Shielding for Safe Offline Reinforcement Learning
by: Galesloot, Maris F. L., et al.
Published: (2026)

Reinforcement Learning with Stochastic Reward Machines
by: Corazza, Jan, et al.
Published: (2025)

Reducing Risk for Assistive Reinforcement Learning Policies with Diffusion Models
by: Tytarenko, Andrii
Published: (2024)

Unveiling Stochasticity: Universal Multi-modal Probabilistic Modeling for Traffic Forecasting
by: Xiong, Weijiang, et al.
Published: (2026)

Composing Reinforcement Learning Policies, with Formal Guarantees
by: Delgrange, Florent, et al.
Published: (2024)