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Ideas
· Adversarial Inverse Reinforcem...
· Interactive MORL
· Reward shaping
· Solution sets in MORL
· Stationary policies
Papers
· Andrychowicz et al. (2018):
Hindsight Experience Replay
· Basaklar et al. (2023):
PD-MORL: Preference-Driven Mul...
· Böhmer et al. (2019):
Exploration with Unreliable In...
· Lu et al. (2023):
Inferring Preferences from Dem...
· Moffaert et al. (2013):
Scalarized multi-objective rei...
· Peschl et al. (2021):
MORAL: Aligning AI with Human ...
· Reyes et al. (2022):
Curiosity-Driven Multi-Agent E...
· Roijers et al. (2020):
Interactive multi-objective re...
· Röpke et al. (2023):
Distributional multi-objective...
· Röpke et al. (2024):
Divide and Conquer: Provably U...
· Siddique et al. (2020):
Learning Fair Policies in Mult...
· Yang et al. (2020):
CM3: Cooperative Multi-goal Mu...
Tag: #paper
12 items with this tag.
2020
CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning
#paper
#rl
#multi-agent
2021
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning
#paper
#rl
#multi-objective
#ethics
2020
Interactive multi-objective reinforcement learning in multi-armed bandits for any utility function
#paper
#rl
#multi-objective
2023
Distributional multi-objective decision making
#paper
2024
Divide and Conquer: Provably Unveiling the Pareto Front with Multi-Objective Reinforcement Learning
#paper
#rl
#multi-objective
2020
Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards
#paper
2013
Scalarized multi-objective reinforcement learning: Novel design techniques
#paper
#rl
#multi-objective
2023
Inferring Preferences from Demonstrations in Multi-objective Reinforcement Learning: A Dynamic Weight-based Approach
#paper
#rl
#multi-objective
2023
PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning Algorithm
#paper
#rl
#multi-objective
2019
Exploration with Unreliable Intrinsic Reward in Multi-Agent Reinforcement Learning
#paper
#rl
#multi-agent
2022
Curiosity-Driven Multi-Agent Exploration with Mixed Objectives
#paper
#rl
#multi-agent
2018
Hindsight Experience Replay
#paper
#rl