Search Results - "Hayes, Conor F"

A practical guide to multi-objective reinforcement learning and planning by 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.

“…Real-world sequential decision-making tasks are generally complex, requiring trade-offs between multiple, often conflicting, objectives. Despite this, the…”
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Actor-critic multi-objective reinforcement learning for non-linear utility functions by Reymond, Mathieu, Hayes, Conor F., Steckelmacher, Denis, Roijers, Diederik M., Nowé, Ann

“…We propose a novel multi-objective reinforcement learning algorithm that successfully learns the optimal policy even for non-linear utility functions…”
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Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021) by Vamplew, Peter, Smith, Benjamin J., Källström, Johan, Ramos, Gabriel, Rădulescu, Roxana, Roijers, Diederik M., Hayes, Conor F., Heintz, Fredrik, Mannion, Patrick, Libin, Pieter J. K., Dazeley, Richard, Foale, Cameron

“…The recent paper “Reward is Enough” by Silver, Singh, Precup and Sutton posits that the concept of reward maximisation is sufficient to underpin all…”
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Monte Carlo tree search algorithms for risk-aware and multi-objective reinforcement learning by Hayes, Conor F., Reymond, Mathieu, Roijers, Diederik M., Howley, Enda, Mannion, Patrick

“…In many risk-aware and multi-objective reinforcement learning settings, the utility of the user is derived from a single execution of a policy. In these…”
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Expected scalarised returns dominance: a new solution concept for multi-objective decision making by Hayes, Conor F., Verstraeten, Timothy, Roijers, Diederik M., Howley, Enda, Mannion, Patrick

“…Abstract In many real-world scenarios, the utility of a user is derived from a single execution of a policy. In this case, to apply multi-objective…”
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Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning by Reymond, Mathieu, Hayes, Conor F., Willem, Lander, Rădulescu, Roxana, Abrams, Steven, Roijers, Diederik M., Howley, Enda, Mannion, Patrick, Hens, Niel, Nowé, Ann, Libin, Pieter

“…Infectious disease outbreaks can have a disruptive impact on public health and societal processes. As decision-making in the context of epidemic mitigation is…”
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Multi-objective Reinforcement Learning: A Tool for Pluralistic Alignment by Vamplew, Peter, Hayes, Conor F, Foale, Cameron, Dazeley, Richard, Harland, Hadassah

“…Reinforcement learning (RL) is a valuable tool for the creation of AI systems. However it may be problematic to adequately align RL based on scalar rewards if…”
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Distributional Multi-Objective Decision Making by Röpke, Willem, Hayes, Conor F, Mannion, Patrick, Howley, Enda, Nowé, Ann, Roijers, Diederik M

“…For effective decision support in scenarios with conflicting objectives, sets of potentially optimal solutions can be presented to the decision maker. We…”
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Monte Carlo Tree Search Algorithms for Risk-Aware and Multi-Objective Reinforcement Learning by Hayes, Conor F, Reymond, Mathieu, Roijers, Diederik M, Howley, Enda, Mannion, Patrick

“…In many risk-aware and multi-objective reinforcement learning settings, the utility of the user is derived from a single execution of a policy. In these…”
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From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Models by Nisioti, Eleni, Glanois, Claire, Najarro, Elias, Dai, Andrew, Meyerson, Elliot, Pedersen, Joachim Winther, Teodorescu, Laetitia, Hayes, Conor F, Sudhakaran, Shyam, Risi, Sebastian

“…Large Language Models (LLMs) have taken the field of AI by storm, but their adoption in the field of Artificial Life (ALife) has been, so far, relatively…”
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Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making by Hayes, Conor F, Verstraeten, Timothy, Roijers, Diederik M, Howley, Enda, Mannion, Patrick

“…In many real-world scenarios, the utility of a user is derived from the single execution of a policy. In this case, to apply multi-objective reinforcement…”
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Multi-Objective Coordination Graphs for the Expected Scalarised Returns with Generative Flow Models by Hayes, Conor F, Verstraeten, Timothy, Roijers, Diederik M, Howley, Enda, Mannion, Patrick

“…Many real-world problems contain multiple objectives and agents, where a trade-off exists between objectives. Key to solving such problems is to exploit sparse…”
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Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning by Vamplew, Peter, Foale, Cameron, Hayes, Conor F, Mannion, Patrick, Howley, Enda, Dazeley, Richard, Johnson, Scott, Källström, Johan, Ramos, Gabriel, Rădulescu, Roxana, Röpke, Willem, Roijers, Diederik M

“…Research in multi-objective reinforcement learning (MORL) has introduced the utility-based paradigm, which makes use of both environmental rewards and a…”
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Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search by Hayes, Conor F, Reymond, Mathieu, Roijers, Diederik M, Howley, Enda, Mannion, Patrick

“…In many risk-aware and multi-objective reinforcement learning settings, the utility of the user is derived from the single execution of a policy. In these…”
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Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning by Reymond, Mathieu, Hayes, Conor F, Willem, Lander, Rădulescu, Roxana, Abrams, Steven, Roijers, Diederik M, Howley, Enda, Mannion, Patrick, Hens, Niel, Nowé, Ann, Libin, Pieter

“…Infectious disease outbreaks can have a disruptive impact on public health and societal processes. As decision making in the context of epidemic mitigation is…”
Get full text

Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021) by Vamplew, Peter, Smith, Benjamin J, Kallstrom, Johan, Ramos, Gabriel, Radulescu, Roxana, Roijers, Diederik M, Hayes, Conor F, Heintz, Fredrik, Mannion, Patrick, Libin, Pieter J. K, Dazeley, Richard, Foale, Cameron

“…The recent paper `"Reward is Enough" by Silver, Singh, Precup and Sutton posits that the concept of reward maximisation is sufficient to underpin all…”
Get full text

A Practical Guide to Multi-Objective Reinforcement Learning and Planning by 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

“…Auton Agent Multi-Agent Syst 36, 26 (2022) Real-world decision-making tasks are generally complex, requiring trade-offs between multiple, often conflicting,…”
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