README_temperature.md

Overview

temperature.py implements the Temperature system, a crucial component of the Copycat system that controls the balance between exploration and exploitation during analogical reasoning. It provides various formulas for adjusting probabilities based on the current temperature, which affects how the system makes decisions.

Core Components

Temperature class: Main class that manages the temperature system
Multiple adjustment formulas for probability modification
Temperature history tracking

Key Features

Manages temperature-based control of the reasoning process
Provides multiple formulas for probability adjustment
Supports temperature clamping and unclamping
Tracks temperature history and differences
Allows dynamic switching between adjustment formulas

Adjustment Formulas

original: Basic temperature-based adjustment
entropy: Entropy-based adjustment
inverse: Inverse weighted adjustment
fifty_converge: Convergence to 0.5
soft_curve: Soft curve adjustment
weighted_soft_curve: Weighted soft curve
alt_fifty: Alternative fifty convergence
average_alt: Averaged alternative
best: Working best formula
sbest: Soft best formula
pbest: Parameterized best
meta: Meta-level adjustment
pmeta: Parameterized meta
none: No adjustment

Main Methods

update(value): Update temperature value
clampUntil(when): Clamp temperature until specified time
tryUnclamp(currentTime): Attempt to unclamp temperature
value(): Get current temperature
getAdjustedProbability(value): Get temperature-adjusted probability
useAdj(adj): Switch to different adjustment formula

Dependencies

Uses math for mathematical operations
Used by the main copycat module

Notes

Temperature starts at 100.0 and can be clamped
Lower temperatures encourage more conservative decisions
Higher temperatures allow more exploratory behavior
The system tracks average differences between adjusted and original probabilities
Different adjustment formulas can be used for different reasoning strategies

2.1 KiB Raw Blame History