论文标题
MARTI-4：人类大脑的新模型，考虑新皮层和基底神经节 - 学会通过在单个CPU上进行加强学习来玩Atari游戏
MARTI-4: new model of human brain, considering neocortex and basal ganglia -- learns to play Atari game by reinforcement learning on a single CPU
论文作者
论文摘要
我们提出了深层控制 - 皮质 - 纹状体脑回路的新ML结构，它们将整个皮质柱用作结构元素，而不是新的神经元。基于这种建筑，我们提出了Marti-考虑新皮层和基底神经节的新模型。该模型被解开以实现权宜之计，并能够在未知环境中学习和实现目标。我们介绍了一种新颖的惊喜感觉机制，可以通过内在的奖励大大改善强化学习过程。我们使用OpenAI健身房环境在几个小时内就在单个CPU上展示了Marti学习。
We present Deep Control - new ML architecture of cortico-striatal brain circuits, which use whole cortical column as a structural element, instead of a singe neuron. Based on this architecture, we present MARTI - new model of human brain, considering neocortex and basal ganglia. This model is de-signed to implement expedient behavior and is capable to learn and achieve goals in unknown environments. We introduce a novel surprise feeling mechanism, that significantly improves reinforcement learning process through inner rewards. We use OpenAI Gym environment to demonstrate MARTI learning on a single CPU just in several hours.
