All Toolsโ€บMemory Decay Simulation Tool
๐Ÿ”ง Local AI memory managementJune 9, 2026โœ… Tests passing

Memory Decay Simulation Tool

A CLI tool to simulate and visualize memory decay in AI systems. Developers can test different decay strategies, analyze how memory diminishes over time, and optimize configurations for their AI workflows.

What It Does

  • Simulate exponential and linear memory decay.
  • Visualize memory decay using matplotlib.
  • Save the decay plot as an image file.

Installation

1. Clone the repository:

git clone <repository_url>
   cd memory_decay_simulator

2. Install the required dependencies:

pip install -r requirements.txt

Usage

Run the CLI tool with the following arguments:

python memory_decay_simulator.py --strategy <strategy> --rate <rate> --duration <duration>

Arguments

  • --strategy: Decay strategy (exponential or linear).
  • --rate: Decay rate (positive float).
  • --duration: Duration of the simulation (positive integer).

Example

Simulate exponential decay with a rate of 0.05 over 100 time units:

python memory_decay_simulator.py --strategy exponential --rate 0.05 --duration 100

Source Code

import argparse
import numpy as np
import matplotlib.pyplot as plt

def exponential_decay(rate, duration):
    """Simulate exponential memory decay."""
    time = np.arange(0, duration + 1)
    memory = np.exp(-rate * time)
    return time, memory

def linear_decay(rate, duration):
    """Simulate linear memory decay."""
    time = np.arange(0, duration + 1)
    memory = np.maximum(1 - rate * time, 0)
    return time, memory

def simulate_decay(strategy, rate, duration):
    """Simulate memory decay based on the given strategy."""
    if strategy == "exponential":
        return exponential_decay(rate, duration)
    elif strategy == "linear":
        return linear_decay(rate, duration)
    else:
        raise ValueError("Unsupported strategy. Choose 'exponential' or 'linear'.")

def plot_decay(time, memory, strategy, rate, duration):
    """Plot memory decay over time."""
    plt.figure(figsize=(8, 5))
    plt.plot(time, memory, label=f"{strategy.capitalize()} Decay (rate={rate})")
    plt.title("Memory Decay Simulation")
    plt.xlabel("Time")
    plt.ylabel("Memory Retention")
    plt.ylim(0, 1.1)
    plt.grid(True)
    plt.legend()
    plt.savefig("memory_decay_simulation.png")
    plt.show()

def main():
    parser = argparse.ArgumentParser(
        description="Memory Decay Simulation Tool"
    )
    parser.add_argument(
        "--strategy", 
        type=str, 
        choices=["exponential", "linear"], 
        required=True, 
        help="Decay strategy: 'exponential' or 'linear'"
    )
    parser.add_argument(
        "--rate", 
        type=float, 
        required=True, 
        help="Decay rate (positive float)"
    )
    parser.add_argument(
        "--duration", 
        type=int, 
        required=True, 
        help="Duration of the simulation (positive integer)"
    )

    args = parser.parse_args()

    if args.rate <= 0 or args.duration <= 0:
        print("Error: Rate and duration must be positive values.")
        return

    try:
        time, memory = simulate_decay(args.strategy, args.rate, args.duration)
        plot_decay(time, memory, args.strategy, args.rate, args.duration)
    except ValueError as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    main()

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Details

Tool Name
memory_decay_simulator
Category
Local AI memory management
Generated
June 9, 2026
Tests
Passing โœ…
Fix Loops
2

Quick Install

Clone just this tool:

git clone --depth 1 --filter=blob:none --sparse \
  https://github.com/ptulin/autoaiforge.git
cd autoaiforge
git sparse-checkout set generated_tools/2026-06-09/memory_decay_simulator
cd generated_tools/2026-06-09/memory_decay_simulator
pip install -r requirements.txt 2>/dev/null || true
python memory_decay_simulator.py
Memory Decay Simulation Tool โ€” AI Tools by AutoAIForge