Concurrent Q-learning: Reinforcement learning for dynamic goals and environments von Ollington, Robert B., Vamplew, Peter W.

Volltext

Weblogs for market research: Improving opinion detection using system fusion von Osman, D.J., Yearwood, J.L., Vamplew, P.W.

Volltext

A Survey of Multi-Objective Sequential Decision-Making von Roijers, D. M., Vamplew, P., Whiteson, S., Dazeley, R.

Volltext

Survey of intrusion detection systems: techniques, datasets and challenges von Khraisat, Ansam, Gondal, Iqbal, Vamplew, Peter, Kamruzzaman, Joarder

Volltext

Empirical evaluation methods for multiobjective reinforcement learning algorithms von Vamplew, Peter, Dazeley, Richard, Berry, Adam, Issabekov, Rustam, Dekker, Evan

Volltext

A Novel Ensemble of Hybrid Intrusion Detection System for Detecting Internet of Things Attacks von Khraisat, Ansam, Gondal, Iqbal, Vamplew, Peter, Kamruzzaman, Joarder, Alazab, Ammar

Volltext

On the Limitations of Scalarisation for Multi-objective Reinforcement Learning of Pareto Fronts von Vamplew, Peter, Yearwood, John, Dazeley, Richard, Berry, Adam

Volltext

Assessing the impact of griefing in MMORPGs using self-determination theory von Achterbosch, Leigh, Vamplew, Peter, March, Evita

Volltext

Explainable reinforcement learning for broad-XAI: a conceptual framework and survey von Dazeley, Richard, Vamplew, Peter, Cruz, Francisco

Volltext

A practical guide to multi-objective reinforcement learning and planning von Hayes, Conor F., Rădulescu, Roxana, Bargiacchi, Eugenio, Källström, Johan, Macfarlane, Matthew, Reymond, Mathieu, Verstraeten, Timothy, Zintgraf, Luisa M., Dazeley, Richard, Heintz, Fredrik, Howley, Enda, Irissappane, Athirai A., Mannion, Patrick, Nowé, Ann, Ramos, Gabriel, Restelli, Marcello, Vamplew, Peter, Roijers, Diederik M.

Volltext

Hybrid Intrusion Detection System Based on the Stacking Ensemble of C5 Decision Tree Classifier and One Class Support Vector Machine von Khraisat, Ansam, Gondal, Iqbal, Vamplew, Peter, Kamruzzaman, Joarder, Alazab, Ammar

Volltext

Softmax exploration strategies for multiobjective reinforcement learning von Vamplew, Peter, Dazeley, Richard, Foale, Cameron

Volltext

Elastic step DQN: A novel multi-step algorithm to alleviate overestimation in Deep Q-Networks von Ly, Adrian, Dazeley, Richard, Vamplew, Peter, Cruz, Francisco, Aryal, Sunil

Volltext

Explainable robotic systems: understanding goal-driven actions in a reinforcement learning scenario von Cruz, Francisco, Dazeley, Richard, Vamplew, Peter, Moreira, Ithan

Volltext

Potential-based multiobjective reinforcement learning approaches to low-impact agents for AI safety von Vamplew, Peter, Foale, Cameron, Dazeley, Richard, Bignold, Adam

Volltext

The impact of environmental stochasticity on value-based multiobjective reinforcement learning von Vamplew, Peter, Foale, Cameron, Dazeley, Richard

Volltext

Steering approaches to Pareto-optimal multiobjective reinforcement learning von Vamplew, Peter, Issabekov, Rustam, Dazeley, Richard, Foale, Cameron, Berry, Adam, Moore, Tim, Creighton, Douglas

Volltext

An Evaluation Methodology for Interactive Reinforcement Learning with Simulated Users von Bignold, Adam, Cruz, Francisco, Dazeley, Richard, Vamplew, Peter, Foale, Cameron

Volltext

A taxonomy of griefer type by motivation in massively multiplayer online role-playing games von Achterbosch, Leigh, Miller, Charlynn, Vamplew, Peter

Volltext

An online scalarization multi-objective reinforcement learning algorithm: TOPSIS Q-learning von Mirzanejad, Mohammad, Ebrahimi, Morteza, Vamplew, Peter, Veisi, Hadi

Volltext