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Diederik M. Roijers

  1. Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021)
    2021/11/25 by Peter Vamplew, Benjamin J. Smith, Vamplew, Peter +21 · 6 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Receptor Mechanisms and Signaling #Computational Drug Discovery Methods
  2. The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
    2023/03/06 by Raphaël Avalos, Florent Delgrange, Avalos, Raphael +7 · 4 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics
  3. Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning
    2022/04/11 by Mathieu Reymond, Reymond, Mathieu, Conor F. Hayes +19 · 2 citations
    Mathematics · Medicine · Psychology · #Artificial Intelligence (cs.AI) #COVID-19 and Mental Health #COVID-19 epidemiological studies #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Populations and Evolution (q-bio.PE) #Viral Infections and Outbreaks Research
  4. Monte Carlo Tree Search Algorithms for Risk-Aware and Multi-Objective Reinforcement Learning
    2022/11/23 by Conor F. Hayes, Hayes, Conor F., Mathieu Reymond +7 · 2 citations
    Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #Advanced Bandit Algorithms Research #Reinforcement Learning in Robotics
  5. Learning Directed Locomotion in Modular Robots with Evolvable Morphologies
    2020/01/21 by Gongjin Lan, Lan, Gongjin, Matteo De Carlo +9 · 2 citations
    Computer Science · Engineering · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Modular Robots and Swarm Intelligence #Neural and Evolutionary Computing (cs.NE) #Reinforcement Learning in Robotics #Robot Manipulation and Learning
  6. Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search
    2021/02/01 by Conor F. Hayes, Hayes, Conor F., Mathieu Reymond +7 · 1 citation
    Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Games #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics #Simulation Techniques and Applications
  7. MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning
    2024/07/23 by Florian Felten, Umut Ucak, Felten, Florian +23 · 1 voice
    Computer Science · #Artificial Intelligence (cs.AI) #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Multiagent Systems (cs.MA) #cs.AI #cs.GT #cs.MA
  8. Preference Communication in Multi-Objective Normal-Form Games
    2021/11/17 by Willem Röpke, Röpke, Willem, Diederik M. Roijers +5 · 1 citation
    Decision Sciences · Social Sciences · #Auction Theory and Applications #Computer Science and Game Theory (cs.GT) #Experimental Behavioral Economics Studies #FOS: Computer and information sciences #Game Theory and Applications #Machine Learning (cs.LG) #Multiagent Systems (cs.MA)
  9. Bridging the Gap Between Single and Multi Objective Games
    2023/01/13 by Willem Röpke, Carla Groenland, Röpke, Willem +7 · 1 citation
    Decision Sciences · Economics, Econometrics and Finance · #Auction Theory and Applications #Computer Science and Game Theory (cs.GT) #Economic theories and models #FOS: Computer and information sciences #Game Theory and Applications