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CS 234 assignment 2-ALL ANSWERS 100% CORRECT
- Exam (elaborations) • 8 pages • 2021
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Consider the following grid environment. Starting from any unshaded square, you can move up, 
down, left, or right. Actions are deterministic and always succeed (e.g. going left from state 16 goes 
to state 15) unless they will cause the agent to run into a wall. The thicker edges indicate walls, and 
attempting to move in the direction of a wall results in staying in the same square (e.g. going in 
any direction other than left from state 16 stays in 16). Taking any action from the green target...
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CS 234 assignment 2 ALL ANSWERS 100% CORRECT Study Guide
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CS 234 assignment 2 ALL ANSWERS 100% CORRECT Study Guide
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CS 234 assignment 2-ALL ANSWERS 100% CORRECT
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CS 234 Winter 2021: Assignment #2 
Due date: 
Part 1 (0-4): February 5, 2021 at 6 PM (18:00) PST 
Part 2 (5-6): February 12, 2021 at 6 PM (18:00) PST 
These questions require thought, but do not require long answers. Please be as concise as possible. 
We encourage students to discuss in groups for assignments. We ask that you abide by the university 
Honor Code and that of the Computer Science department. If you have discussed the problems with 
others, please include a statement saying who you ...
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CS 234 ASSIGNMENT 2 2021/2022.
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CS 234 
ASSIGNMENT 2 
2021/2022. Introduction 
In this assignment we will implement deep Q-learning, following DeepMind’s paper ([1] and [2]) that learns 
to play Atari games from raw pixels. The purpose is to demonstrate the effectiveness of deep neural networks 
as well as some of the techniques used in practice to stabilize training and achieve better performance. In 
the process, you’ll become familiar with PyTorch. We will train our networks on the Pong-v0 environment 
from OpenAI gym, ...
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CS 234 assignment 2 Latest-ALL ANSWERS 100% CORRECT Study Guide
- Exam (elaborations) • 12 pages • 2022
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CS 234 Winter 2022: Assignment #2 
 
 
 
Introduction 
In this assignment we will implement deep Q-learning, following DeepMind’s paper ([1] and [2]) that learns to play Atari games from raw pixels. The purpose is to demonstrate the effectiveness of deep neural networks as well as some of the techniques used in practice to stabilize training and achieve better performance. In the process, you’ll become familiar with PyTorch. We will train our networks on the Pong-v0 environment from OpenAI g...
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CS 234 assignment 2-ALL ANSWERS 100% CORRECT latest Jan 2022
- Exam (elaborations) • 10 pages • 2021
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Due date: 2/06 (Wed) 11:59 PM (23:59) PST 
These questions require thought, but do not require long answers. Please be as concise as possible. 
We encourage students to discuss in groups for assignments. We ask that you abide by the university 
Honor Code and that of the Computer Science department. If you have discussed the problems with 
others, please include a statement saying who you discussed problems with. Failure to follow these 
instructions will be reported to the Oce of Community Sta...
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2023 Winter CS 234 assignment 2-ALL Questions and ANSWERS 100% CORRECT Verified and Updated Exam Highgraded
- Exam (elaborations) • 15 pages • 2023
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2023 Winter CS 234 assignment 2-ALL Questions and ANSWERS 100% CORRECT Verified and Updated Exam Highgraded2023 Winter CS 234 assignment 2-ALL Questions and ANSWERS 100% CORRECT Verified and Updated Exam Highgraded2023 Winter CS 234 assignment 2-ALL Questions and ANSWERS 100% CORRECT Verified and Updated Exam Highgraded2023 Winter CS 234 assignment 2-ALL Questions and ANSWERS 100% CORRECT Verified and Updated Exam Highgraded2023 Winter CS 234 assignment 2-ALL Questions and ANSWERS 100% CORR...
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CS 234 Winter 2020 Assignment 1 Due: January 22 at 11:59 pm
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CS 234 Winter 2020 
Assignment 1 
Due: January 22 at 11:59 pm
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CS 234 Winter 2020: Assignment #2
- Exam (elaborations) • 13 pages • 2022
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CS 234 Winter 2020: Assignment #2 
 
 
 
Introduction 
In this assignment we will implement deep Q-learning, following DeepMind’s paper ([mnih2015human] and [mnih-atari-2013]) that learns to play Atari games from raw pixels. The purpose is to demonstrate the effectiveness of deep neural networks as well as some of the techniques used in practice to stabilize training and achieve better performance. In the process, you’ll become familiar with TensorFlow. We will train our networks on the Pong...
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