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Variable Speed Limit (VSL) is a traffic control approach that optimises the mainstream traffic on motorways. Reinforcement Learning approach to VSL has been shown to achieve improvements in controlling the mainstream traffic bottleneck on motorways. However, single-agent VSL, applied to a shorter motorway segment, can produce a discontinuity in traffic flow by causing the significant differences in speeds between the uncontrolled upstream flow and the flow affected by VSL. A multi-agent control strategy can be used to overcome these problems by assigning speed limits in multiple upstream motorway sections enabling smoother speed transition. In this paper, we proposed a novel approach to set up multi-agent RL-based VSL by using the W-Learning algorithm (WL-VSL), in which two agents control two segments in the lead up to the congested area. The reward function for each agent is based on the agent's …