This repository contains the source code accompanying the paper “Noise Scheduling and Out-of-Distribution Generalisation in Deep Reinforcement Learning for 6-DOF Robotic Grasping.” The work evaluates three off-policy deep reinforcement learning configurations for a 6-DOF robotic grasping task using a Universal Robots UR5e in the RoboSuite simulation environment: Soft Actor-Critic (SAC) with automatic entropy tuning, Twin Delayed Deep Deterministic Policy Gradient (TD3) with piecewise linear exploration-noise decay, and TD3 with constant Gaussian noise. The repository includes the implementation and experimental setup used to compare training efficiency, in-distribution grasping performance, and out-of-distribution generalisation across the three configurations. The study focuses particularly on the effect of exploration-noise scheduling on policy robustness outside the training distribution.
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al.· Information and Software Tec...· 394 citations· ⚡54
This state-of-practice investigation was performed using a literature review followed by a multiple-case study approach and presents how inconsistency between managerial strategies and execution can lead to failure by means of a behavioral framework.
Carmine Giardino, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 175 citations· ⚡19
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
It is found that roles of MVPs in startups were not fully aware by entrepreneurs, and entrepreneurs should consider a systematic approach to fully explore the value of MVP, as a multiple facet product (MFP).
Anh Nguyen-Duc, P. Abrahamsson· International Conference on...· 93 citations· ⚡9
It is found that what perceived as biggest challenges by software startups do vary across different life cycle stages, even though its significance decreases when the learning focuses of the startups move from problem to solution and their products mature.
Xiaofeng Wang, Henry Edison, Sohaib Shahid Bajwa et al.· International Conference on...· 62 citations· ⚡6
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
A weeklong summer workshop brought higher education faculty to campus to explore how AI and machine learning materials can be adapted for their classrooms.
