Search Results for author:
Found 4 papers, 1 papers with code
A Tale of Two Regulatory Regimes: Creation and Analysis of a Bilingual Privacy Policy Corpus
Over the past decade, researchers have started to explore the use of NLP to develop tools aimed at helping the public, vendors, and regulators analyze disclosures made in privacy policies.
Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications?
Traffic simulators are used to generate data for learning in intelligent transportation systems (ITSs).
UNSAT Solver Synthesis via Monte Carlo Forest Search
We introduce Monte Carlo Forest Search (MCFS), a class of reinforcement learning (RL) algorithms for learning policies in {tree MDPs}, for which policy execution involves traversing an exponential-sized tree.
The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Reality
Traffic signal control (TSC) is a high-stakes domain that is growing in importance as traffic volume grows globally.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
