Intelligent Coordination among Multiple Traffic Intersections Using Multi-Agent Reinforcement Learning

We use Asynchronous Advantage Actor Critic (A3C) for implementing an AI agent in the controllers that optimize flow of traffic across a single intersection and then extend it to multiple intersections by considering a multi-agent setting. We explore three different methodologies to address the multi-agent problem - (1) use of asynchronous property of A3C to control multiple intersections using a single agent (2) utilise self/competitive play among independent agents across multiple intersections and (3) ingest a global reward function among agents to introduce cooperative behavior between intersections... (read more)

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Methods used in the Paper


METHOD TYPE
Entropy Regularization
Regularization
Dense Connections
Feedforward Networks
Softmax
Output Functions
Convolution
Convolutions
A3C
Policy Gradient Methods