---
title: "Define Boltzmann machine"
subject: "Artificial Intelligence"
chapter: 6
key: "semester_6/artificial_intelligence:define-boltzmann-machine"
source: https://www.bctengineer.com/q/semester_6/artificial_intelligence/define-boltzmann-machine
site: BCT Engineering
---

# Define Boltzmann machine

Artificial Intelligence · Chapter 6: Machine Learning

- Asked in: 2070 Magh, 1 marks
- Video: [Introduction to Boltzmann Machines](https://www.youtube.com/watch?v=1HrOkb-RL0Y) — Juefei Yuan
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_6/artificial_intelligence/define-boltzmann-machine
- Whole chapter: https://www.bctengineer.com/md/semester_6/artificial_intelligence/chapter-6

## Question

Define Boltzmann Machine.

## Short answer

A Boltzmann machine is a stochastic recurrent network of binary units with symmetric weights. Units switch on probabilistically based on energy and temperature. Simulated annealing helps avoid local minima.

## Answer

A **Boltzmann machine** is a stochastic recurrent neural network of symmetrically connected binary units (visible and hidden). Each unit switches on with a probability that depends on its net input and a temperature T, and the network is trained so that its energy function reaches a minimum for the desired patterns; simulated annealing is used to avoid local minima.

## Check yourself

The answer's key points as multiple-choice questions, with the correct option and why.

1. What is a Boltzmann machine?
   A. A stochastic recurrent network of symmetrically connected binary units whose on-probability depends on net input and temperature
   B. A deterministic feed-forward network with no hidden units
   C. A supervised single-neuron classifier
   D. A clustering network using winner-takes-all
   Answer: A. It is stochastic and uses simulated annealing to escape local minima. (Key point: Definition)

2. Why is simulated annealing used?
   A. To make it deterministic
   B. To avoid getting trapped in local energy minima
   C. To remove hidden units
   D. To speed up forward passes only
   Answer: B. Gradually lowering T lets the network settle in a low-energy state. (Key point: Annealing purpose)

3. What are the two kinds of units in a Boltzmann machine?
   A. Input and winner units
   B. Excitatory and inhibitory only
   C. Visible and hidden units
   D. Master and slave units
   Answer: C. Visible units hold input/output; hidden units capture internal representation. (Key point: Unit types)

## Related in Artificial Intelligence

- [Machine learning; Boltzmann machines](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aml-boltzmann-machine) — Artificial Intelligence, chapter 6