Adaptive weighted sum method for multiobjective optimization: a new method for Pareto front generation

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Multiobjective Reinforcement Learning: A Comprehensive Overview (2015, methodology): “a scalar value, including the weighted sum method [14], the constraint method [15], the sequential method [16], and the max-min method, etc.”
A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation (2019, methodology): “The first is to convert the multi-objective problem into a single-objective one through various techniques [3, 4, 5, 6] and use traditional RL algorithms.”
Localized Weighted Sum Method for Many-Objective Optimization (2018, methodology): “Kim and de Weck [69], [70] proposed to first use the WS method to quickly obtain an approximation of the PF, then construct a mesh of Pareto front patches.”