AIBullisharXiv – CS AI · Mar 36/104
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Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents
Researchers have developed SwitchMT, a novel methodology using Spiking Neural Networks with adaptive task-switching for multi-task learning in autonomous agents. The approach addresses task interference issues and demonstrates competitive performance in multiple Atari games while maintaining low power consumption and network complexity.