By adding your voice to the Dinosaur Protection Group, you can help bring global awareness to the extinction event that currently threatens the inhabitants of Isla Nublar. We brought the dinosaurs back into the world; it’s now our responsibility to protect these magnificent creatures. Actually, it’s more than a responsibility. It’s a calling.

The Dinosaur Protection Group, or DPG, is a non-profit organization based in the Mission District of San Francisco that focuses on the preservation of dinosaurs and advocating their rights as a species. [1] In February 2017, the Costa Rican Institute of …

DPGWikia is a collaborative encyclopedia dedicated to the Dinosaur Protection Group from Jurassic World: Fallen Kingdom in the Jurassic Park Franchise that anyone can edit! Read more about Mount Sibo and its threat to destroy all life on Isla Nublar. The Website! http://www.dinosaurprotectiongroup.com/

The DPG and the dinosaurs need your help! Mount Sibo is erupting, threatening to end all life all of the dinosaurs inhabiting Isla Nublar. Save the remaining dinosaurs left on Isla Nublar, and support the Dinosaur Protection Group to save them.

2018年6月16日 · Any insight over the recent years has come to light thanks JUR@55!_H@K3R and Dinosaur Protection Group. What exists below is a list of species cloned by InGen and recovered documents by JUR@55!_H@K3R.

This category goes for all of the dinosaurs, endangered, extinct, or missing (A.K.A cryptids).

DPG是最早的一篇文章，主要从理论的角度提出了一种deterministic、off-policy的policy gradient算法，并给出了policy gradient的计算公式和参数更新方法。 DQN在DPG后一年发表，主要是解决了用神经网络拟合 Q函数 （也就是action-value函数）导致的训练不稳定的问题。

文章给出的解决办法是设计一个off-policy的算法，让stochastic behaviour policy去负责探索，而determinisitc traget policy负责学习。 这个离线学习的算法就是将 Off-Policy Actor-Critic 算法中的Stochastic Policy替换成Determinisitic Policy。 关于Off-Policy Actor-Critic请参考我的 强化学习论文笔记 (1) 我们先从Stochastic情况出发，策略梯度的优化目标函数： 对于stochastic policy，策略梯度为： 对于stochastic policy， 一个重要的问题是如何估计 Q^\pi (s,a) 。

采用莫烦的一句话来概括DDPG：Google deepmind提出的一种使用 actor-critic结构，但是输出的不是行为发概率，而是具体的行为，用于连续动作（continuous action）的预测，DDPG结合了之前获得成功的DQN结构，提高了actor-critic是的稳定性和收敛性。 1、与DPG的不同之处

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