mlsanityData to 14 Oct 2026

HEAT:History-Enhanced Dual-phase Actor-Critic Algorithm with A Shared Transformer

arXiv 2504.13193 ↗First posted 13 Apr 2025cs.NI cs.AI cs.LGcited by 0

On the map: Deep reinforcement learning methods → RL for energy, networks and operations

Abstract (arXiv)

For a single-gateway LoRaWAN network, this study proposed a history-enhanced two-phase actor-critic algorithm with a shared transformer algorithm (HEAT) to improve network performance. HEAT considers uplink parameters and often neglected downlink parameters, and effectively integrates offline and online reinforcement learning, using historical data and real-time interaction to improve model performance. In addition, this study developed an open source LoRaWAN network simulator LoRaWANSim. The simulator considers the demodulator lock effect and supports multi-channel, multi-demodulator and bidirectional communication. Simulation experiments show that compared with the best results of all compared algorithms, HEAT improves the packet success rate and energy efficiency by 15% and 95%, respectively.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for energy, networks and operations, one of 15 directions in Deep reinforcement learning methods. Builds on 5 of its 16 references that are in the map. First posted on arXiv 13 Apr 2025.

Builds on

5 of 16 references.

References · 5

  1. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,417
  2. 2021Offline Reinforcement Learning with Implicit Q-Learningcited by 1,293
  3. 2023Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularizationcited by 116
  4. 2023ENOTO: Improving Offline-to-Online Reinforcement Learning with Q-Ensemblescited by 20
  5. 2024Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RLcited by 10

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  4. 2025Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach
  5. 2025A Deep Reinforcement Learning Method for Multi-objective Transmission Switching
  6. 2025Average Reward Reinforcement Learning for Wireless Radio Resource Management
  7. 2025A Communication-Efficient Decentralized Actor-Critic Algorithm
  8. 2025Multi-Agent Reinforcement Learning in Wireless Distributed Networks for 6G