We compared the efficiency of the FlyHash model, an insect-inspired sparse neural network (Dasgupta et al., 2017), to similar but non-sparse models in an embodied navigation task. This requires a model to control steering by comparing current visual inputs to memories stored along a training route. We concluded the FlyHash model is more efficient than others, especially in terms of data encoding.

翻译：我们比较了FlyHash模型（一种受昆虫启发的稀疏神经网络，Dasgupta等人，2017年）与类似但非稀疏模型在具身导航任务中的效率。该任务要求模型通过将当前视觉输入与沿训练路径存储的记忆进行比较来控制转向。我们得出结论，FlyHash模型比其他模型更高效，尤其是在数据编码方面。