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Patrick Mannion
Patrick Mannion
Lecturer Above the Bar / Assistant Professor in Computer Science, NUI Galway
Verified email at nuigalway.ie - Homepage
Title
Cited by
Cited by
Year
Deep Reinforcement Learning for Autonomous Driving: A Survey
BR Kiran, I Sobh, V Talpaert, P Mannion, AA Al Sallab, Yogamani, Senthil, ...
IEEE Transactions on Intelligent Transportation Systems, 2021
3382021
An Experimental Review of Reinforcement Learning Algorithms for Adaptive Traffic Signal Control
P Mannion, J Duggan, E Howley
Autonomic Road Transport Support Systems, 47-66, 2016
2372016
Multi-objective multi-agent decision making: a utility-based analysis and survey
R Radulescu, P Mannion, DM Roijers, A Nowé
Autonomous Agents and Multi-Agent Systems 34 (10), 2020
622020
Exploring applications of deep reinforcement learning for real-world autonomous driving systems
V Talpert, I Sobh, BR Kiran, P Mannion, S Yogamani, A El-Sallab, P Perez
International Conference on Computer Vision Theory and Applications (VISAPP), 2019
482019
Parallel Reinforcement Learning for Traffic Signal Control
P Mannion, J Duggan, E Howley
The 4th International Workshop on Agent-based Mobility, Traffic and …, 2015
412015
Policy Invariance under Reward Transformations for Multi-Objective Reinforcement Learning
P Mannion, S Devlin, K Mason, J Duggan, E Howley
Neurocomputing 263, 60-73, 2017
362017
Dynamic Economic Emissions Dispatch Optimisation using Multi-Agent Reinforcement Learning
P Mannion, K Mason, S Devlin, J Duggan, E Howley
Adaptive and Learning Agents workshop (at AAMAS 2016), 2016
292016
Applying Multi-Agent Reinforcement Learning to Watershed Management
K Mason, P Mannion, J Duggan, E Howley
Adaptive and Learning Agents workshop (at AAMAS 2016), 2016
252016
A practical guide to multi-objective reinforcement learning and planning
CF Hayes, R Rădulescu, E Bargiacchi, J Källström, M Macfarlane, ...
Autonomous Agents and Multi-Agent Systems 36 (26), 2022
242022
Reward shaping for knowledge-based multi-objective multi-agent reinforcement learning
P Mannion, S Devlin, J Duggan, E Howley
The Knowledge Engineering Review 33 (e23), 2018
232018
Multi-Objective Dynamic Dispatch Optimisation using Multi-Agent Reinforcement Learning
P Mannion, K Mason, S Devlin, J Duggan, E Howley
Proceedings of the 15th International Conference on Autonomous Agents and …, 2016
232016
A utility-based analysis of equilibria in multi-objective normal form games
R Radulescu, P Mannion, Y Zhang, DM Roijers, A Nowé
The Knowledge Engineering Review 35 (e32), 2020
182020
Applying Q(λ)-learning in Deep Reinforcement Learning to Play Atari Games
SS Mousavi, M Schukat, P Mannion, E Howley
Adaptive and Learning Agents workshop (at AAMAS 2017), 2017
152017
Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games
Y Zhang, R Radulescu, P Mannion, DM Roijers, A Nowé
Proceedings of the 19th International Conference on Autonomous Agents and …, 2020
142020
Distributional Monte Carlo Tree Search for Risk-Aware and Multi-Objective Reinforcement Learning
CF Hayes, M Reymond, DM Roijers, E Howley, P Mannion
Proceedings of the 20th International Conference on Autonomous Agents and …, 2021
112021
A Theoretical and Empirical Analysis of Reward Transformations in Multi-Objective Stochastic Games
P Mannion, J Duggan, E Howley
Proceedings of the 16th International Conference on Autonomous Agents and …, 2017
112017
Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search
CF Hayes, M Reymond, DM Roijers, E Howley, P Mannion
Adaptive and Learning Agents Workshop (at AAMAS 2021), 2021
92021
Opponent learning awareness and modelling in multi-objective normal form games
R Radulescu, T Verstraeten, Y Zhang, P Mannion, DM Roijers, A Nowé
Neural Computing and Applications, 2022
82022
Learning Traffic Signal Control with Advice
P Mannion, J Duggan, E Howley
Adaptive and Learning Agents workshop (at AAMAS 2015), 2015
82015
Equilibria in Multi-Objective Games: a Utility-Based Perspective
R Radulescu, P Mannion, DM Roijers, A Nowé
Adaptive and Learning Agents Workshop (at AAMAS 2019), 2019
72019
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