ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps
Conflict Mitigation (ConMit) is a crucial part of intelligent network control in Open Radio Access Networks (O-RAN). In this paper, we propose a method named ACCoRD to resolve detected control conflicts in Near-Real Time RAN Intelligent Controller using a Conflict Resolution (CR) Agent with an Artificial Neural Network (ANN) trained with a reinforcement learning algorithm PPO-Clip. The implemented ANN analyzes data about the network and conflicting control decisions to infer optimal CR actions. The CR Agent gathers feedback from the network after each resolved conflict to assess its efficiency and adjust the ANN's weights during batch training. The evaluation of the proposed approach is b...
| Authors | Cezary Adamczyk, Adrian Kliks |
|---|---|
| Primary category | cs.MA |
| Published | 21 May 2026 |
| Last updated at source | 21 May 2026 |
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