AI & MACHINE LEARNING PROGRAM • LEVEL 24 — REINFORCEMENT LEARNING

Choose an Epsilon-greedy Action with Python

Learn choose an epsilon-greedy action with python with a short, executable Python example.

IntermediateEpsilon greedyExploration

PROBLEM UNDERSTANDING

Input and expected output

Sample input

No input required

Sample output

left

COMPLETE PYTHON PROGRAM

Complete Python implementation

import random
random.seed(1)
actions=['left','right']
q=[1,3]
epsilon=0.2
choice=random.choice(actions) if random.random()<epsilon else actions[q.index(max(q))]
print(choice)

CURRENT STEP

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SELECTED LINE

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EXPECTED OUTPUT FOR THE SAMPLE

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0%Step 0 of 0

PROGRAM EXPLANATION

Algorithm and explanation

Import the required standard-library tools and prepare the sample data for choose an epsilon-greedy action.
Apply Epsilon greedy and Exploration to compute the required result.
Display the result for choose an epsilon-greedy action and compare it with the documented sample output.

This example of choose an epsilon-greedy action computes the result directly from the prepared sample data. It demonstrates Epsilon greedy and Exploration and prints a deterministic result that can be checked against the sample output.

EFFICIENCY

Time and space complexity

Time complexity

O(n)

Auxiliary space

O(1)

DEBUGGING CHECKLIST

Common mistakes

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For choose an epsilon-greedy action, keep the data shape and value types consistent with Epsilon greedy.

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Keep every dependent statement inside the correct indented Python block.

Check this

Verify the final Epsilon greedy and Exploration result against the sample before trying new data.

Try it yourself

Practice: Run the program with the sample input, predict its output, and then test one boundary case of your own.