Models ToT prompting as a DAG and introduces DSAC to optimize thought assignment in edge-enabled AIGC, achieving up to 8.32% delay reduction over PPO in simulations while cutting latency over 80% versus local execution.
Asynchronous methods for deep reinforcement learning,
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Unleashing the Power of Tree-of-Thoughts for Edge-Enabled AIGC Service Provisioning
Models ToT prompting as a DAG and introduces DSAC to optimize thought assignment in edge-enabled AIGC, achieving up to 8.32% delay reduction over PPO in simulations while cutting latency over 80% versus local execution.