Artificial Intelligence Interview Questions – Set 15

by

What are some of the algorithms used for hyperparameter optimization?

There are many algorithms that are used for hyperparameter optimization, and following are the three main ones that are widely used:

  • Bayesian optimization
  • Grid search
  • Random search

Mention the difference between breadth first search and best first search in artificial intelligence?

These are the two strategies which are quite similar. In best first search, we expand the nodes in accordance with the evaluation function. While, in breadth first search a node is expanded in accordance to the cost function of the parent node.

What is the Minimax Algorithm? Explain the terminologies involved in a Minimax problem.

Minimax is a recursive algorithm used to select an optimal move for a player assuming that the other player is also playing optimally.

A game can be defined as a search problem with the following components:

  • Game Tree: A tree structure containing all the possible moves.
  • Initial state: The initial position of the board and showing whose move it is.
  • Successor function: It defines the possible legal moves a player can make.
  • Terminal state: It is the position of the board when the game ends.
  • Utility function: It is a function which assigns a numeric value for the outcome of a game.

What’s a feature vector?

A feature vector is an n-dimensional vector that contains essential information that describes the characteristics of an object. For example, it can be an object’s numerical features or a list of numbers taken from the output of a neural network layer.

In AI and data science, feature vectors can be used to represent numeric or symbolic characteristics of an object in mathematical terms for seamless analysis.

Let’s break this down. A data set is usually organized into multiple examples where each example will have several features. However, a feature vector won’t have the same feature for numerous examples. Instead, each example will correspond to one feature vector that will contain all the numerical values for that example object.

Feature vectors are often stacked into a design matrix. In this scenario, each row will be a feature vector for one example. Each column will feature all the examples that correspond to that particular feature. This means that it will be like a matrix, but with just one row and multiple columns (or a single column and multiple rows) like [1,2,3,5,6,3,2,0].

How are game theory and AI related?

AI system uses game theory for enhancement; it requires more than one participant which narrows the field quite a bit. The two fundamental roles are as follows:

  •  Participant design: Game theory is used to enhance the decision of a participant to get maximum utility.
  •  Mechanism design: Inverse game theory designs a game for a group of intelligent participants, e.g., auctions.

What is a Chatbot?

A chatbot is Artificial intelligence software or agent that can simulate a conversation with humans or users using Natural language processing. The conversation can be achieved through an application, website, or messaging apps. These chatbots are also called as the digital assistants and can interact with humans in the form of text or through voice.

The AI chatbots are broadly used in most businesses to provide 24*7 virtual customer support to their customers, such as HDFC Eva chatbot, Vainubot, etc.

Explain Karl Pearson’s Coefficient of Correlation?

Karl Pearson’s correlation coefficient is a measure of the strength of a linear association between two variables.
It is denoted by r or rxy (where x and y being the two variables involved).
This method of correlation draws a line of best fit through the data of two variables.
The value of the Pearson correlation coefficient (r) indicates how far away all these data points are to this line of best fit.

Formula –

Artificial Intelligence formula
Where,
* cov(X, Y): is the covariance between X and Y

What is user Interface?

Generally, ES users and ES itself uses User interface as a medium of interaction between users. Also, the user of the ES need not be necessarily an expert in Artificial Intelligence.
Although, at a particular recommendation, it explains how the ES has arrived. Hence, the explanation may appear in the following forms −

  • Basically, the natural language displayed on a screen.
  • Also, verbal narrations in natural language.
    Further, listing of rule numbers displayed on the screen. The user interface makes it easy to trace the credibility of the deductions.

What Brute-Force Search Strategies?

This strategy doesn’t require any domain-specific knowledge. Thus it’s so simple strategy. Hence, it works very smoothly and fine with a small number of possible states.

Requirements for Brute Force Algorithms

a. State description

b. A set of valid operators

c. Initial state

d. Goal state description

What is AI?

is a field of computer science wherein the cognitive functions of the human brain are studied and replicated on a machine or a system. Artificial Intelligence today is widely used in various sectors of the economy including science and technology, healthcare, telecommunications, energy and so on. AI has three different levels:

  • Narrow AI: AI is narrow when the machine performs a specific task better than a human. The current research of AI is taking place at this level.
  • General AI: AI reaches the general state when it can perform any intellectual task equivalent to the accuracy of that of a human.
  • Active AI: AI is active when it can completely beat humans in all performed tasks.