Paradigms on English AI Terms Dictionary

Computational intelligence

Sat, 18 Jul 2026 09:51:20 +0000

Definition

Computational intelligence (CI) encompasses a set of nature-inspired computational paradigms, including neural networks, fuzzy logic, and evolutionary computation. These systems are designed to handle uncertainty, imprecision, and partial truth in problem-solving scenarios. CI focuses on learning from data and adapting to changing environments, making it particularly useful for control systems, pattern recognition, and optimization tasks where traditional algorithmic approaches may fail due to complexity or lack of precise models.

AI agent

Sat, 18 Jul 2026 09:43:55 +0000

Definition

An AI agent is a software entity that operates autonomously within a defined environment to accomplish predefined objectives. It utilizes perception mechanisms to gather data, processes this information using reasoning models, and executes actions via actuators or APIs. Unlike passive models, agents can plan, learn from feedback, and adapt their behavior over time, making them suitable for complex tasks requiring decision-making and interaction with dynamic systems.

Summary

An autonomous system designed to perceive its environment and take actions to achieve specific goals.

Supervised Learning

Sat, 18 Jul 2026 09:42:48 +0000

Definition

In supervised learning, the algorithm is trained on a labeled dataset, meaning each input example is paired with the correct output. The goal is for the model to learn the underlying relationship between inputs and outputs so it can accurately predict labels for unseen data. Common tasks include classification, where discrete categories are predicted, and regression, where continuous values are estimated.

Summary

A machine learning paradigm where a model learns to map inputs to outputs based on labeled training examples.

Large Language Models

Sat, 18 Jul 2026 09:33:34 +0000

Definition

This term refers to the broader application paradigm where models with billions of parameters are leveraged for zero-shot or few-shot learning across diverse linguistic tasks. Unlike specialized models, LLMs serve as general-purpose engines that can be prompted to perform various functions without task-specific retraining, shifting the focus from model architecture design to prompt engineering and fine-tuning strategies.

Summary

The paradigm of using scaled neural networks for broad-spectrum natural language understanding and generation tasks.

Driven

Sat, 18 Jul 2026 09:31:32 +0000

Definition

The term ‘driven’ is commonly used as a suffix to indicate the primary force or mechanism behind an AI approach. For instance, ‘data-driven’ implies decisions are made based on statistical patterns in data rather than explicit programming, while ‘goal-driven’ suggests actions are optimized to maximize a specific reward signal, as seen in reinforcement learning. It highlights the foundational paradigm of the system, distinguishing between rule-based logic and emergent behaviors derived from inputs or optimization targets.

Agents

Sat, 18 Jul 2026 09:30:04 +0000

Definition

AI agents are software programs or systems capable of perceiving their surroundings through sensors (inputs), processing information, and executing actions via actuators (outputs) to achieve defined objectives. They operate autonomously within an environment, often employing reasoning, planning, and learning capabilities to navigate complex tasks, make decisions, and interact with other agents or humans effectively.

Summary

Autonomous entities that perceive their environment and take actions to achieve specific goals.

Key Concepts

Perception
Autonomy
Goal-Oriented
Actuation

Use Cases

Chatbots
Autonomous Vehicles
Trading Bots

Paradigms on English AI Terms Dictionary

Computational intelligence

Definition

AI agent

Definition

Summary

Supervised Learning

Definition

Summary

Large Language Models

Definition

Summary

Driven

Definition

Agents

Definition

Summary

Key Concepts

Use Cases

Related Terms