A Practical Guide to Multi-Objective Reinforcement Learning and Planning

1 code implementation • 17 Mar 2021 • Conor F. Hayes, Roxana Rădulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers

Real-world decision-making tasks are generally complex, requiring trade-offs between multiple, often conflicting, objectives.

Decision Making Multi-Objective Reinforcement Learning +1

Leveraging GPT-2 for Classifying Spam Reviews with Limited Labeled Data via Adversarial Training

1 code implementation • 24 Dec 2020 • Athirai A. Irissappane, Hanfei Yu, Yankun Shen, Anubha Agrawal, Gray Stanton

Online reviews are a vital source of information when purchasing a service or a product.

Spam detection

EasyRL: A Simple and Extensible Reinforcement Learning Framework

no code implementations • 4 Aug 2020 • Neil Hulbert, Sam Spillers, Brandon Francis, James Haines-Temons, Ken Gil Romero, Benjamin De Jager, Sam Wong, Kevin Flora, Bowei Huang, Athirai A. Irissappane

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.

OpenAI Gym reinforcement-learning +1

GANs for Semi-Supervised Opinion Spam Detection

2 code implementations • 19 Mar 2019 • Gray Stanton, Athirai A. Irissappane

Online reviews have become a vital source of information in purchasing a service (product).

General Classification Generative Adversarial Network +3

Scaling POMDPs For Selecting Sellers in E-markets-Extended Version

no code implementations • 30 Nov 2015 • 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).