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Which of the following is true about reinforcement learning?
The agent gets rewards or penalty according to the action
The agent navigates in an environmental building the example experiences or the training dataset.
The target of an agent is to maximize the rewards and minimize the penalty.
All of the above
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1 Reinforcement Learning - Introduction to Reinforcement Learning
2 MCQ - In Reinforcement Learning, a software agent makes observations, takes actions within an environment, and receives rewards in return
3 MCQ - A policy is the algorithm used by software agent to determine its actions.
4 MCQs- Reinforcement learning is -
5 MCQs - Which of the following is true about reinforcement learning?
6 Reinforcement Learning - Introduction to OpenAI Gym
7 MCQ - OpenAI gym is a toolkit that provides wide variety of simulations to train agents in Reinforcement Learning
8 Reinforcement Learning - Credit Assignment Problem (Part I)
9 Reinforcement Learning - Credit Assignment Problem (Part II)
10 MCQ - An action advantage is the estimate of how much better or worse an action is compared to other possible actions, on average
11 MCQ -REINFORCE algorithms were introduced by Ronald Williams in
12 Reinforcement Learning - Markov Decision Processes
13 MCQ - Markov Chains are stochastic processes with no memory
14 MCQs - Hidden Markov Model is used in Reinforcement learning.
15 Reinforcement Learning - Value Iteration Algorithm, Q-Value
16 Reinforcement Learning - Temporal Difference Learning
17 Reinforcement Learning - Q-Learning
18 MCQ - Q-Learning algorithm is off-policy algorithm because
19 MCQ - DNN that estimates Q-Values is called Deep Q-Network (DQN)
20 MCQ - The Dueling DQN algorithm was introduced in yet another 2015 paper by
21 Reinforcement Learning - TF-Agents Library
22 MCQ - TF-Agents library is a Reinforcement Learning library based on TensorFlow
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