CreateAMind

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用户1908973

Carla Challenge比赛

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用户1908973

腾讯paper 模仿学习

3. 基于分批历史数据的指数加权模仿学习方法 Exponentially Weighted Imitation Learning for Batched H...

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用户1908973

planet 介绍

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用户1908973

STCN

https://www.arxiv-vanity.com/papers/1902.06568/

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用户1908973

Motion Selective Prediction for Video Frame Synthesis

https://www.arxiv-vanity.com/papers/1812.10157/

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用户1908973

拆解特斯拉AP2.0/2.5运算单元看未来无人驾驶域控制器的设计趋势2

结合对DriveWorks的实际应用和性能评测,Autopilot2.0这样的硬件架构,到底能完成几级的自动驾驶呢?在此,做一些分析和分解。

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用户1908973

从特斯拉AP2.0/2.5 运算单元看未来无人驾驶域控制器的设计趋势1

新悦智行从今年4 月份开始设计自己的WiseADCU 无人驾驶运算控制单元,所以做了一些同类产品的对标和分析。因为WiseADCU 已经投板,所以将...

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用户1908973

ppo trained carla demo show and method

Our dream is creating a safe driving system working well under all circumstance,...

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用户1908973

Planet paper and note

The latest paper from Google, improve learning efficiency 50+ times

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用户1908973

SQN(看最后的视频里 砖块被打光了)及代码及saved_models

再看LunarLander-v2的效果(也是比较简单了。。。),AverageEpRet就是不上300... : (

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用户1908973

解决RL好奇心探索后遗忘的问题

Amplifying the Imitation Effect for Reinforcement Learning of

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用户1908973

从经验学习以加强探索

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用户1908973

动物脑的好奇心和强化学习的好奇心

Visual novelty, curiosity, and intrinsic reward in machine learning and the brai...

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用户1908973

RND 实验 跑了17个房间

https://github.com/openai/random-network-distillation

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用户1908973

Playing MontezumaRevenge with RND 含视频

https://github.com/openai/random-network-distillation

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用户1908973

Control is important! model predictive control mpc.pytorch lib

Optimal control is a widespread field that involve finding an optimal sequence o...

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用户1908973

强化学习的 bayes 探索

1 openai RND:https://blog.openai.com/reinforcement-learning-with-prediction-base...

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用户1908973

模仿学习 比较图

ONE-SHOT HIGH-FIDELITY IMITATION: TRAINING LARGE-SCALE DEEP NETS WITH RL

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用户1908973

无监督学习 比较图

Luke Metz Google Brain lmetz@google.com Niru Maheswaranathan Google Brain nirum...

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用户1908973

Model-Based 两篇paper

Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based C...

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