Empirical Evaluation of Multi-Agent Routing Approaches. - Adriaan ter Mors; Cees Witteveen; Charlotte Ipema; Frits de Nijs; Theodor Tsiourakis (IAT, 2012)

Evaluation and Improvement of Laruelle-Widgrén Inverse Banzhaf Approximation - Frits de Nijs; Daan Wilmer (CoRR, 2012)

A Novel Priority Rule Heuristic: Learning from Justification. - Frits de Nijs; Tomas Klos (ICAPS, 2014)

Best-Response Planning of Thermostatically Controlled Loads under Power Constraints. - Frits de Nijs; Matthijs T. J. Spaan; Mathijs de Weerdt (AAAI, 2015)

Dynamic Capacity Control and Balancing in the Medium Voltage Grid. - Frits de Nijs (AAMAS, 2015)

Decoupling a Resource Constraint Through Fictitious Play in Multi-Agent Sequential Decision Making. - Frits de Nijs; Matthijs T. J. Spaan; Mathijs Michiel de Weerdt (ECAI, 2016)

Bounding the Probability of Resource Constraint Violations in Multi-Agent MDPs. - Frits de Nijs; Erwin Walraven; Mathijs Michiel de Weerdt; Matthijs T. J. Spaan (AAAI, 2017)

Preallocation and Planning Under Stochastic Resource Constraints. - Frits de Nijs; Matthijs T. J. Spaan; Mathijs Michiel de Weerdt (AAAI, 2018)

Capacity-aware Sequential Recommendations. - Frits de Nijs; Georgios Theocharous; Nikos Vlassis; Mathijs Michiel de Weerdt; Matthijs T. J. Spaan (AAMAS, 2018)

Resource-constrained Multi-agent Markov Decision Processes. - Frits de Nijs (2019)

Risk-Aware Conditional Replanning for Globally Constrained Multi-Agent Sequential Decision Making. - Frits de Nijs; Peter J. Stuckey (AAMAS, 2020)

Large Neighborhood Search for Temperature Control with Demand Response. - Edward Lam 001; Frits de Nijs; Peter J. Stuckey; Donald Azuatalam; Ariel Liebman (CP, 2020)

Reinforcement Learning for Strategic Recommendations. - Georgios Theocharous; Yash Chandak; Philip S. Thomas; Frits de Nijs (CoRR, 2020)

Evaluating Meta-Reinforcement Learning through a HVAC Control Benchmark (Student Abstract). - Yashvir S. Grewal; Frits de Nijs; Sarah Goodwin (AAAI, 2021)

Constrained Multiagent Markov Decision Processes: a Taxonomy of Problems and Algorithms. - Frits de Nijs; Erwin Walraven; Mathijs Michiel de Weerdt; Matthijs T. J. Spaan (J. Artif. Intell. Res., 2021)

Proximal Policy Optimization Based Reinforcement Learning for Joint Bidding in Energy and Frequency Regulation Markets. - Muhammad Anwar; Changlong Wang; Frits de Nijs; Hao Wang 016 (CoRR, 2022)

Comparison and Evaluation of Methods for a Predict+Optimize Problem in Renewable Energy. - Christoph Bergmeir; Frits de Nijs; Abishek Sriramulu; Mahdi Abolghasemi; Richard Bean 001; John M. Betts; Quang Bui; Nam Trong Dinh; Nils Einecke; Rasul Esmaeilbeigi; Scott Ferraro; Priya Galketiya; et al. (CoRR, 2022)

Exploring Hydrogen Supply/Demand Networks: Modeller and Domain Expert Views. - Matthias Klapperstueck; Frits de Nijs; Ilankaikone Senthooran; Jack Lee-Kopij; Maria Garcia de la Banda; Michael Wybrow (CP, 2023)

Model-Free Approach to Fair Solar PV Curtailment Using Reinforcement Learning. - Zhuo Wei; Frits de Nijs; Jinhao Li 001; Hao Wang 016 (e-Energy, 2023)

Residential Power and Battery Data. - Christoph Bergmeir; Quang Bui; Frits de Nijs; Peter J. Stuckey (Zenodo, 2023)

Human-in-the-Loop AI for HVAC Management Enhancing Comfort and Energy Efficiency. - Xinyu Liang; Frits de Nijs; Buser Say; Hao Wang 016 (e-Energy, 2025)

Using Assistance Rewards Without Introducing Bias: Overcoming Sparse Rewards in Multi-Agent Reinforcement Learning. - Yue Yang; Bernd Meyer 001; Frits de Nijs (AAMAS, 2025)

Predict+Optimize Problem in Renewable Energy Scheduling. - Christoph Bergmeir; Frits de Nijs; Evgenii Genov; Abishek Sriramulu; Mahdi Abolghasemi; Richard Bean 001; John M. Betts; Quang Bui; Nam Trong Dinh; Nils Einecke; Rasul Esmaeilbeigi; Scott Ferraro; et al. (IEEE Access, 2025)

Learning to cooperate against ensembles of diverse opponents. - Isuri Perera; Frits de Nijs; Julian García (Neural Comput. Appl., 2025)