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Xiaohui Tu

xiaohui.tu@mila.quebec
Doctorat - HEC
Superviseur⋅e principal⋅e
Erick Delage
Sujets de recherche
Apprentissage par renforcement
Optimisation

Publications

Fair Policy Optimization in Major-Minor Weakly Coupled Markov Decision Processes
Xiaohui Tu
Yossiri Adulyasak
Erick Delage
We consider fair resource allocation in sequential decision-making environments modeled as major-minor weakly coupled Markov decision proces… (voir plus)ses (M2WCMDP). In this framework, resource constraints couple the action spaces of a major sub-Markov decision process (sub-MDP) and a population of minor sub-MDPs that would otherwise operate independently. Instead of using the traditional utilitarian (total-sum) objective, we optimize a general class of monotone, concave, permutation-invariant, normalized fairness functions. With homogeneous minor sub-MDPs, we prove that the problem under symmetry reduces to optimizing the platform-plus-mean-participant utilitarian objective over the class of \textit{permutation-invariant} policies, which allows us to exploit efficient algorithms that optimize the utilitarian-based objective to solve this fairness-aware problem. For more general settings, we introduce a count-proportion-based deep reinforcement learning approach with a priority-based sampler that generates feasible count actions. The generality of our framework means that the proposed algorithms and theoretical guarantees transfer to any domain with a symmetric M2WCMDP structure. We consider two applications: the machine replacement problem and the joint control of pricing and taxi relocation problem on a New York City-calibrated dataset. We validate our theoretical findings with comprehensive experiments, confirming the effectiveness of our proposed method in achieving strong fairness-aware performance while remaining scalable.
2026-09-27
arXiv (prépublication)
doi.org
arxiv.org
Fair Resource Allocation in Weakly Coupled Markov Decision Processes
Xiaohui Tu
Yossiri Adulyasak
Nima Akbarzadeh
Erick Delage
We consider fair resource allocation in sequential decision-making environments modeled as weakly coupled Markov decision processes, where r… (voir plus)esource constraints couple the action spaces of
2025-05-02
International Conference on Artificial Intelligence and Statistics (Accept (Poster))
doi.org
proceedings.mlr.press