A conceptual framework for externally-influenced agents: an assisted reinforcement learning review

Autor: Richard Dazeley, Francisco Cruz, Peter Vamplew, Matthew D. Taylor, Tim Brys, Cameron Foale, Adam Bignold

Publikováno v: Journal of Ambient Intelligence and Humanized Computing. 14:3621-3644

A long-term goal of reinforcement learning agents is to be able to perform tasks in complex real-world scenarios. The use of external information is one way of scaling agents to more complex problems. However, there is a general lack of collaboration

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f4dd6ca8ecd57822569b02e88ad42fa0
https://doi.org/10.1007/s12652-021-03489-y

Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees

Autor: Dennis Soemers, Tim Brys, Kurt Driessens, Mark Winands, Ann Nowé

Publikováno v: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, February 2-7, 2018: The Thirtieth AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-18), 7831-7836
STARTPAGE=7831;ENDPAGE=7836;TITLE=Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, February 2-7, 2018
Vrije Universiteit Brussel
Maastricht University

Credit card transactions predicted to be fraudulent by automated detection systems are typically handed over to human experts for verification. To limit costs, it is standard practice to select only the most suspicious transactions for investigation.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3986dbc04a043b8d2600a1d35ce03b0f
https://cris.maastrichtuniversity.nl/en/publications/473cc83b-0cfc-4d08-acb5-e1e7b351a6d1

Human Guided Ensemble Learning in StarCraft

Autor: Timothy Verstraeten, Roxana Rădulescu, Yannick Jadoul, Tom Jaspers, Robrecht Conjaerts, Tim Brys, Anna Harutyunyan, Peter Vrancx, Ann Nowe

Publikováno v: Vrije Universiteit Brussel

In reinforcement learning, agents are typically only rewarded based on the task requirements. However, in complex environments, such reward schemes are not informative enough to efficiently learn the optimal strategy. Previous literature shows that f

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::42506ac801eddc61889d0f8a790f32d8
https://biblio.vub.ac.be/vubir/human-guided-ensemble-learning-in-starcraft(6387150e-f183-446e-a40e-ab3ad45c72b1).html

Departure MANagement with a Reinforcement Learning Approach: Respecting CFMU Slots

Autor: Thierry Salvant, Ivomar Brito Soares, Tim Brys, Kris Januarius, Yann-Michaël De Hauwere, Ann Nowé

Publikováno v: ITSC

This paper considers how existing Reinforcement Learning (RL) techniques can be used to model and learn solutions for large scale Multi-Agent Systems (MAS). The large scale MAS of interest is the context of the movement of departure flights in big ai

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fe9af35aa3358b6ac6ddf0f26f0b73f
https://doi.org/10.1109/itsc.2015.193

Ensembles of Shapings

Autor: Tim Brys, Anna Harutyunyan, Taylor, Matthew E., Ann Nowe

Publikováno v: Vrije Universiteit Brussel

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::904fc09d7e715d45d2488fcd2d0e5f4a
https://biblio.vub.ac.be/vubir/ensembles-of-shapings(4146b007-cf3d-4d69-aaf6-e02c10154cb3).html