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simmediumoffline-rlmetric · varies

Decision SpikeFormer: Spike-Driven Transformer for Decision Making

Description

Offline reinforcement learning (RL) enables policy training solely on pre-collected data, avoiding direct environment interaction - a crucial benefit for energy-constrained embodied AI applications. Although Artificial Neural Networks (ANN)-based methods perform well in offline RL, their high computational and energy demands motivate exploration of more efficient alternatives. Spiking Neural Networks (SNNs) show promise for such tasks, given their low power consumption. In this work, we introduc

Source

http://arxiv.org/abs/2504.03800v1