Cover Image

Efficient Stimuli Generation using Reinforcement Learning in Design Verification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gadde, Deepak Narayan, Nalapat, Thomas, Kumar, Aman, Lettnin, Djones, Kunz, Wolfgang, Simon, Sebastian
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving Simulation Regression Efficiency using a Machine Learning-based Method in Design Verification
by: Gadde, Deepak Narayan, et al.
Published: (2024)

FuzzWiz -- Fuzzing Framework for Efficient Hardware Coverage
by: Gadde, Deepak Narayan, et al.
Published: (2024)

Saarthi: The First AI Formal Verification Engineer
by: Kumar, Aman, et al.
Published: (2025)

Hey AI, Generate Me a Hardware Code! Agentic AI-based Hardware Design & Verification
by: Gadde, Deepak Narayan, et al.
Published: (2025)

All Artificial, Less Intelligence: GenAI through the Lens of Formal Verification
by: Gadde, Deepak Narayan, et al.
Published: (2024)

Verifying Non-friendly Formal Verification Designs: Can We Start Earlier?
by: Olmos, Bryan, et al.
Published: (2024)

Generative AI Augmented Induction-based Formal Verification
by: Kumar, Aman, et al.
Published: (2024)

Effective Design Verification -- Constrained Random with Python and Cocotb
by: Gadde, Deepak Narayan, et al.
Published: (2024)

Optimizing Coverage-Driven Verification Using Machine Learning and PyUVM: A Novel Approach
by: Kumari, Suruchi, et al.
Published: (2025)

Agentic AI-based Coverage Closure for Formal Verification
by: Pothireddypalli, Sivaram, et al.
Published: (2026)

Knowledge Graphs, the Missing Link in Agentic AI-based Formal Verification
by: Viswambharan, Vaisakh Naduvodi, et al.
Published: (2026)

Towards Efficient Design Verification -- Constrained Random Verification using PyUVM
by: Gadde, Deepak Narayan, et al.
Published: (2024)

Saarthi for AGI: Towards Domain-Specific General Intelligence for Formal Verification
by: Kumar, Aman, et al.
Published: (2026)

A Semi-Formal Verification Methodology for Efficient Configuration Coverage of Highly Configurable Digital Designs
by: Kumar, Aman, et al.
Published: (2024)

Accelerated Online Reinforcement Learning using Auxiliary Start State Distributions
by: Mehra, Aman, et al.
Published: (2025)

Curriculum-Guided Antifragile Reinforcement Learning for Secure UAV Deconfliction under Observation-Space Attacks
by: Panda, Deepak Kumar, et al.
Published: (2025)

Formal that "Floats" High: Formal Verification of Floating Point Arithmetic
by: Mohanty, Hansa, et al.
Published: (2025)

Analogous Alignments: Digital "Formally" meets Analog
by: Mohanty, Hansa, et al.
Published: (2024)

Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks
by: Valencia, David, et al.
Published: (2024)

Interpretability by Design for Efficient Multi-Objective Reinforcement Learning
by: Xia, Qiyue, et al.
Published: (2025)

Environment Design for Inverse Reinforcement Learning
by: Buening, Thomas Kleine, et al.
Published: (2022)

Generative Adversarial Evasion and Out-of-Distribution Detection for UAV Cyber-Attacks
by: Panda, Deepak Kumar, et al.
Published: (2025)

Sample-Efficient Constrained Reinforcement Learning with General Parameterization
by: Mondal, Washim Uddin, et al.
Published: (2024)

GenCircuit-RL: Reinforcement Learning from Hierarchical Verification for Genetic Circuit Design
by: Flynn, Noah
Published: (2026)

FPGA Divide-and-Conquer Placement using Deep Reinforcement Learning
by: Wang, Shang, et al.
Published: (2024)

Reinfier and Reintrainer: Verification and Interpretation-Driven Safe Deep Reinforcement Learning Frameworks
by: Yang, Zixuan, et al.
Published: (2024)

Empirical Design in Reinforcement Learning
by: Patterson, Andrew, et al.
Published: (2023)

The Role of Emotional Stimuli and Intensity in Shaping Large Language Model Behavior
by: Patel, Ameen, et al.
Published: (2026)

Reinforcement Learning via Auxiliary Task Distillation
by: Harish, Abhinav Narayan, et al.
Published: (2024)

Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence
by: Zhu, Lingwei, et al.
Published: (2023)

Sample and Computationally Efficient Continuous-Time Reinforcement Learning with General Function Approximation
by: Zhao, Runze, et al.
Published: (2025)

Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems
by: Marfo, William, et al.
Published: (2025)

Efficient Preference-Based Reinforcement Learning: Randomized Exploration Meets Experimental Design
by: Schlaginhaufen, Andreas, et al.
Published: (2025)

Stable Reinforcement Learning for Efficient Reasoning
by: Dai, Muzhi, et al.
Published: (2025)

RL-ACRGNet: Reinforcement Learning-Based Chest Radiology Report Generation Network
by: Meena, Yogesh Kumar, et al.
Published: (2026)

Thermodynamics of Reinforcement Learning Curricula
by: Adamczyk, Jacob, et al.
Published: (2026)

Meta Policy Switching for Secure UAV Deconfliction in Adversarial Airspace
by: Panda, Deepak Kumar, et al.
Published: (2025)

ReACT: Reinforcement Learning for Controller Parametrization using B-Spline Geometries
by: Rudolf, Thomas, et al.
Published: (2024)

A Differential Perspective on Distributional Reinforcement Learning
by: Rojas, Juan Sebastian, et al.
Published: (2025)

Horizon Generalization in Reinforcement Learning
by: Myers, Vivek, et al.
Published: (2025)