Q: 1 Which of the following is not a type of artificial intelligence agent?
Simple AI Agent
Unity Based AI Agent
Learning AI Agent
Goal Based AI Agent
[ Option B ]
In Artificial Intelligence, an agent is an entity that perceives its environment through sensors and acts upon that environment using actuators.
Common types of AI agents include Simple Reflex Agents, Model-Based Agents, Goal-Based Agents, Utility-Based Agents, and Learning Agents.
A Learning AI Agent improves its performance by learning from past experiences, and a Goal-Based AI Agent selects actions to achieve specific goals. However, Unity Based AI Agent is not a recognized type of AI agent in artificial intelligence theory.
| TYPE OF AI AGENT | DESCRIPTION |
|---|---|
| Simple Reflex Agent | Acts only based on the current percept (input) using condition–action rules. Does not consider past states. |
| Model-Based Agent | Maintains an internal model of the environment to handle partially observable situations. |
| Goal-Based Agent | Chooses actions that help achieve specific goals using search or planning. |
| Utility-Based Agent | Selects actions based on a utility function to achieve the best possible outcome among alternatives. |
| Learning Agent | Improves its performance over time by learning from experience and feedback. |
Q: 2 In Chat GPT, GPT stands for
Generative Pre-trained Transformer
Generative Process Trainer
General Processor Transformer
General Pre-training Transformer
[ Option A ]
ChatGPT is based on a type of artificial intelligence model designed for understanding and generating human-like text. The GPT stands for Generative Pre-trained Transformer. The term GPT describes the working nature of this model.
“GENERATIVE” means it can generate or create new content, “PRE-TRAINED” means it is trained on large amounts of data before being used for specific tasks, and “TRANSFORMER” refers to the deep learning architecture used to process and understand language.
Q: 3 Two finite state machines are said to be equivalent if
Both have same number of edges
Both have same number of states
Both recognize the same set of tokens
Both have same number of edges and states
[ Option C ]
Two Finite State Machines (FSMs) are considered equivalent if they produce the same output behavior for all possible inputs.
In the case of automata theory, this means both machines accept or recognize the same language (set of strings/tokens), even if their internal structure (number of states or transitions) is different.
Q: 4 A decision tree in AI can be used for
Only classification tasks
Only regression tasks
Both classification and regression tasks
Neither classification nor regression tasks
[ Option C ]
A Decision Tree is a supervised machine learning algorithm used for predictive modeling. It represents decisions and their possible outcomes in the form of a tree structure, where internal nodes represent tests on attributes, branches represent outcomes of the tests, and leaf nodes represent final predictions.
Decision trees can be used for classification tasks, where the output is a discrete class label (spam or not spam), and for regression tasks, where the output is a continuous numerical value (predicting house prices). Therefore, decision trees are suitable for both classification and regression problems.
Q: 5 AI based National Language Translation mission by Govt. of India is
Bhashini
Bhuvan
Bhasha
Babel
[ Option A ]
The Government of India has launched an AI-based language translation initiative called Bhashini under the National Language Translation Mission (NLTM).
Its aim is to enable easy access to digital services and content in multiple Indian languages using Artificial Intelligence (AI) and Natural Language Processing (NLP).
Q: 6 Which of the following is advantage of Artificial Intelligence?
Identifying a business trend to help in informed decision making
Helps in analysis of cyber security incidents
Based on learning capability, solves a pattern recognition problem
All of the above
[ Option D ]
Artificial Intelligence (AI) provides several advantages in different fields. It can identify business trends and patterns in large datasets, which helps organizations make better and informed decisions.
AI is also widely used in cybersecurity, where it helps analyze and detect unusual activities or security incidents quickly.
In addition, AI systems have learning capabilities, allowing them to recognize patterns and solve complex problems such as image recognition, speech recognition, and data classification.
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