mlsanityData to 14 Oct 2026

Regularized Soft Actor-Critic for Behavior Transfer Learning

arXiv 2209.13224 ↗First posted 27 Sep 2022cs.LGcited by 1

On the map: Offline RL and imitation learning from data → Imitation learning methods

Abstract (arXiv)

Existing imitation learning methods mainly focus on making an agent effectively mimic a demonstrated behavior, but do not address the potential contradiction between the behavior style and the objective of a task. There is a general lack of efficient methods that allow an agent to partially imitate a demonstrated behavior to varying degrees, while completing the main objective of a task. In this paper we propose a method called Regularized Soft Actor-Critic which formulates the main task and the imitation task under the Constrained Markov Decision Process framework (CMDP). The main task is defined as the maximum entropy objective used in Soft Actor-Critic (SAC) and the imitation task is defined as a constraint. We evaluate our method on continuous control tasks relevant to video games applications.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Imitation learning methods, one of 13 directions in Offline RL and imitation learning from data. Builds on 9 of its 15 references that are in the map. First posted on arXiv 27 Sep 2022.

Builds on

9 of 15 references.

References · 9

  1. 2016Generative Adversarial Imitation Learningcited by 1,597
  2. 2017Reinforcement Learning with Deep Energy-Based Policiescited by 669
  3. 2017Learning Robust Rewards with Adversarial Inverse Reinforcement Learningcited by 490
  4. 2020Projection-Based Constrained Policy Optimizationcited by 203
  5. 2019A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptationcited by 177
  6. 2018Dynamic Weights in Multi-Objective Deep Reinforcement Learningcited by 100
  7. 2016Multi-Objective Deep Reinforcement Learningcited by 83
  8. 2020Safe Reinforcement Learning via Curriculum Inductioncited by 74
  9. 2018A Large-Scale Study on Regularization and Normalization in GANscited by 26

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Cited by year

Citing papers per year: 2023: 1.

1 paper.

  1. 2023Policy Diversity for Cooperative Agentscited by 2

Similar, not cited

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  1. 2023Coherent Soft Imitation Learning
  2. 2025Unlocking the Potential of Soft Actor-Critic for Imitation Learning
  3. 2021Offline Reinforcement Learning with Soft Behavior Regularization
  4. 2024Generalizing soft actor-critic algorithms to discrete action spaces
  5. 2025Learning safe, constrained policies via imitation learning: Connection to Probabilistic Inference and a Naive Algorithm
  6. 2025Effective Reinforcement Learning Control using Conservative Soft Actor-Critic
  7. 2025IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
  8. 2022Model-Based Imitation Learning Using Entropy Regularization of Model and Policy