4 papers
Fairness-Aware Performance Evaluation for Multi-Party Multi-Objective Optimization
Zifan Zhao, Peilan Xu, Wenjian Luo
In multiparty multiobjective optimization problems, solution sets are usually evaluated using classical performance metrics, aggregated across DMs. However, such mean-based evaluat…
MIR: Efficient Exploration in Episodic Multi-Agent Reinforcement Learning via Mutual Intrinsic Reward
Kesheng Chen, Wenjian Luo, Bang Zhang +2
Episodic rewards present a significant challenge in reinforcement learning. While intrinsic reward methods have demonstrated effectiveness in single-agent rein-forcement learning s…
Decomposability-Guaranteed Cooperative Coevolution for Large-Scale Itinerary Planning
Ziyu Zhang, Peilan Xu, Yuetong Sun +2
Large-scale itinerary planning is a variant of the traveling salesman problem, aiming to determine an optimal path that maximizes the collected points of interest (POIs) scores whi…
Runtime Analysis of Evolutionary Algorithms for Multi-party Multi-objective Optimization
Yuetong Sun, Peilan Xu, Wenjian Luo
In scenarios where multiple decision-makers operate within a common decision space, each focusing on their own multi-objective optimization problem (e.g., bargaining games), the pr…