Generating Unique Pseudo-Random Numbers Within a Class's Function in Python

Learn how to generate unique pseudo-random numbers for your q_table in Python by properly initializing class attributes.
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Generating Unique Pseudo-Random Numbers Within a Class's Function in Python

When working with machine learning algorithms or simulations, generating a unique set of pseudo-random numbers is often crucial. For instance, if you are trying to create multiple instances of a Q-table in Python but end up with identical values, it’s likely due to how you've defined these variables within your class. This post will guide you through the issue, demonstrating how to correctly initialize class attributes for generating distinct random values.

Understanding the Problem

The main issue here arises from how the q_table variable is defined within the class. In the code provided, q_table was declared as a class variable instead of an instance variable. This means that no matter how many instances of the class blob you created, they would all point to the same q_table, resulting in identical values.

Initial Code Review

Here’s a brief look at the problematic portion of the original code:

[[See Video to Reveal this Text or Code Snippet]]

What Went Wrong?

Class Variable vs. Instance Variable: The q_table is defined as a class variable, leading to shared memory across instances (x and z in the example).

The Solution

To resolve this issue, we need to turn q_table into an instance variable. This ensures that each instance of blob creates its own unique q_table. Following this approach, we can utilize the __init__ method, which is called when an instance of the class is created.

Step-by-Step Fix

Define __init__ Method: Move the initialization of q_table to the __init__ method.

Keep init() for Setup: You can keep the existing init method for generating the Q-table values.

Here’s how the updated class might look:

[[See Video to Reveal this Text or Code Snippet]]

What Changed?

The statement q_table = {} is now inside the __init__ method to make it an instance variable.

This adjustment ensures that each object of the blob class has its own independently generated q_table.

Conclusion

By moving the definition of q_table inside the __init__ method, we ensure that each instance of the class holds unique values rather than sharing the same memory location. This is crucial for generating individual sets of random numbers and achieving your goals in simulation or machine learning tasks.

Apply this adjustment to your code, and you will notice that each instance of your blob class generates its own distinct Q-table correctively filled with different random numbers!