19 citations · 24 across the 5 of their papers we have counts for
4 papers · 1 filter
A Practical Guide to Multi-Objective Reinforcement Learning and Planning
Conor F. Hayes, Roxana Rădulescu, Eugenio Bargiacchi +15
Real-world decision-making tasks are generally complex, requiring trade-offs between multiple, often conflicting, objectives. Despite this, the majority of research in reinforcemen…
Leveraging GPT-2 for Classifying Spam Reviews with Limited Labeled Data via Adversarial Training
Athirai A. Irissappane, Hanfei Yu, Yankun Shen +2
Online reviews are a vital source of information when purchasing a service or a product. Opinion spammers manipulate these reviews, deliberately altering the overall perception of…
EasyRL: A Simple and Extensible Reinforcement Learning Framework
Neil Hulbert, Sam Spillers, Brandon Francis +7
In recent years, Reinforcement Learning (RL), has become a popular field of study as well as a tool for enterprises working on cutting-edge artificial intelligence research. To thi…
Scaling POMDPs For Selecting Sellers in E-markets-Extended Version
Athirai A. Irissappane, Frans A. Oliehoek, Jie Zhang
In multiagent e-marketplaces, buying agents need to select good sellers by querying other buyers (called advisors). Partially Observable Markov Decision Processes (POMDPs) have sho…