case+study-stage1-lesson2sub

Stage 1: study MIT course
Learn MIT 6.S094- Deep Learning and Self-Driving Cars Course! Course website: [] ,all slides are videos can be downloaded from this page There are 5 lectures, each about 90 minutes.

Lecture 2: Deep reinforcement learning learning summary deadline 20171206 Material to research: 1. CASE study 2. MIT lecture 2: see [] 3.Reference: work on your deep traffic project: tutorial: https://selfdrivingcars.mit.edu/deeptraffic/ simulation: https://selfdrivingcars.mit.edu/deeptrafficjs/
 * http://www.algorithmdog.com/series/rl-series 强化学习系列文章
 * https://selfdrivingcars.mit.edu/resources/ course resources -- see Deep Reinforcement Learning
 * http://karpathy.github.io/2016/05/31/rl/ Deep Reinforcement Learning: Pong from Pixels
 * https://www.intelnervana.com/demystifying-deep-reinforcement-learning/ 解密强化学习
 * https://deepmind.com/blog/deep-reinforcement-learning/
 * http://cs.stanford.edu/people/karpathy/convnetjs/ ConvNetJS
 * http://cs.stanford.edu/people/karpathy/convnetjs/demo/rldemo.html [|ConvNetJS] Deep Q Learning Demo
 * https://github.com/karpathy/convnetjs/blob/master/build/deepqlearn.js
 * http://cs.stanford.edu/people/karpathy/convnetjs/docs.html last section
 * https://arxiv.org/pdf/1312.5602v1.pdf Playing Atari with Deep Reinforcement Learning
 * https://github.com/parilo/DeepTraffic-solution 75.28mph solution on deep traffic for your reference!

Please cover all the related items in the case study material that you can find in lesson 2.You need to do extensive research. Submit your summary of lesson 2 in the form of PPT, try to use multimedia presentation: list the related key term or item in outline of your PPT and elaborate each one with sufficient materials and summarize it. submit your own deep traffic code:

Submission: HL students
 * Doris:
 * Alex:
 * Tom:
 * Charles:
 * Michael:
 * Enzo:
 * Arthur

(SL Optional)
 * Matt:
 * Margaret:
 * David: