In this article we explain the agent of artificial intelligence or Artificial Intelligence Agent (AI Agent) What is based on what the principles are and what are the benefits of using it. We also explain about the types of artificial intelligence agents and how they work. Finally, we will be introduced to a few examples of AIGent that leading AI companies have developed.
Artificial intelligence
Artificial Intelligence is a software program that has abilities such as interacting with its environment, collecting data, and using data collected for independent tasks. The AI Agent uses these capabilities to achieve the predetermined goals. Humans set goals, but the artificial intelligence agent chooses the best steps needed to achieve those independent goals.
For example, consider the artificial intelligence factor in the call center that aims to solve customer problems. This automatic factor asks the customer different things, searchs the information in internal documents, and responds with a solution. Next, the agent, based on customer’s responses, determines that he can solve the problem or should refer it to the human being.
Key Principles of Definement of Artificial Intelligence
All automatic software perform different tasks according to software developer guidelines, but what causes artificial intelligence or special intelligent factors?
Artificial Intelligence Factors are rational agents (rational agents); That is, based on their own perception and data, they make logical decisions to achieve optimal performance and results. The artificial intelligence agent feels its environment through physical or software interfaces.
For example, the robotics agent collects sensors data, but chats use customer questions instead of input. The artificial intelligence agent uses this data to make a conscious decision. This agent analyzes the collected data to predict the best possible results to achieve the set goals; It can also use these results to plan its next action; For example, cars can identify the barriers on the road based on the data received from multiple sensors and guide their route cleverly.
The benefits of using artificial intelligence agents
The most important benefits of using agents or artificial intelligence agents are as follows:
Increase productivity
Artificial intelligence is the intelligent systems of autonomous systems that perform specific tasks without the need for human intervention. Organizations use these factors to achieve specific goals and more efficient business results. When business teams delegate repetitive tasks to artificial intelligence agents, their productivity increases; Thus factors can focus on creative or very important activities and increase the value of their organization.
Reduce costs
Business owners can reduce unnecessary costs of inefficient processes, human errors, and manual processes using smart agents. You can make sophisticated tasks more secure with the help of artificial intelligence agents; Because autonomous factors follow a constant model that adapts to environmental changes.
Conscious decision
Advanced smart agents use machine learning technology (ML) to collect and process large quantities of instant data. This feature allows business managers to better predict when planning and determining future strategies; For example, when running an advertising campaign, you can use artificial intelligence agents to analyze demand demand in different segments of the market.
Improving customer experience
Customers are looking for personalized and attractive experiences when interacting with businesses. The integration of artificial intelligence agents into customer service systems enables customization of product suggestions for each customer, quick response and innovation in the field of customer interaction, and the conversion of a potential customer to actual and loyal customer.
Artificial intelligence agents
Organizations produce and implement a variety of smart types. Here are some of the most important types of these factors
Simple Reflex Agents (Simple Reflex Agents)
Simple reflection agents act only on their defined rules and instant data. This factor does not react to conditions beyond the rules; So suitable for simple tasks that do not require extensive training; For example, a simple reflection factor can be used to reset the password that performs this process by identifying specific keywords in the user’s conversation.
Model-based Reflex Agents (Model-Based Reflex Agents)
Model -based agents operate similar to simple reflection factors, but it has a more advanced decision -making mechanism. Instead of following a specific law, these factors evaluate the results and possible consequences before deciding. Then, using backup data, it creates an internal model of the world around it and uses it to make better decisions.
Goal-Based Agents (Goal-Based Agents)
Target-based agents, also called “Rule-Based Agents”, have more advanced reasoning capabilities. These factors, in addition to evaluating environmental data, compare different approaches to achieve the best possible results. They always choose the most efficient path. These AI factors are suitable for complicated tasks such as Natural Language Processing (NLP) and robotic applications.
Utility-based agents (Utility-Based Agents)
The useful agent uses sophisticated reasonable algorithms to help users use sophisticated reasonable algorithms. This agent compares different scenarios and their benefits or benefits and selects an option that gives the most reward to the user; For example, customers can use a useful factor to search for flight tickets with the shortest travel time, regardless of price.
Learning Agents (Learning Agents)
The learner is constantly learning from his previous experiences to improve the results. This agent uses sensory inputs and feedback mechanisms to adapt its learning elements to meet specific standards. In addition, to design new tasks, it uses the problem generator to teach it with collected data and past results.
Hierarchical Agents (Hierarchical Agents)
Organized group hierarchical factors are intelligent agents arranged at different levels. Higher level factors divide complex tasks into smaller tasks and entrust them to lower level factors. Every independent factor operates and presents its progress to the regulatory factor. Then, the higher level factor collects the results and manages the coordination between the subsidiary factors to make sure they all act in order to achieve the set goals.
How artificial intelligence works
Artificial intelligence agents do their job by simplifying and automating complex tasks. Most autonomous agents follow a specific workflow when performing tasks, which have 3 steps:
Determination of goals
The artificial intelligence agent takes a specific order or purpose from the user. It then uses this goal to plan tasks that make the end result relevant and useful to the user. Divide the target factor into several smaller and impressive tasks. It then performs these tasks based on specific arrangements or conditions to achieve the goal.
Information collection
Artificial intelligence agents need information to succeed in planned tasks; For example, the factor to succeed in the analysis of the customer’s feelings must extract the conversations; Therefore, artificial intelligence agents can be accessed to search and retrieve the information they need. In some cases, the intelligent agent can interact with other machine learning factors or models to gain more information or exchange data.
Implementation of tasks
The artificial intelligence agent, after collecting sufficient information, performs the desired task smart. When it does the task, it removes it from the list and deals with the next task. During the tasks, the factor evaluates whether or not to achieve the specified goal. It uses external feedback and examines its logs. In this process, the agent may create and execute new tasks to achieve the end result.
Introduction to the objective examples of artificial intelligence agents
In the end, we introduce you to the four objective AI Agent samples built by leading AI companies.
OpenAI -based GPT -based agencies
Openai is the creator of the famous LG Models (LLM) such as Gpt-4O and Openai O1. The company is also one of the pioneers of the Natural Language Processing (NLP) and artificial intelligence.
With the latest version of its models, Openai has developed highly advanced language models that form the basis of autonomous factors in various applications. Research by the organization has enhanced the understanding of the language to a higher level and provides digital agents with opportunities:
- Participate in multi -step conversations
- To identify linguistic delicacies
- Give detailed and detailed answers
Business owners can integrate GPT -based agencies into their platforms through the OPENAI API. These agents can perform a wide range of tasks, including:
- Answering complicated questions
- Help customer service
- Production of creative content
Google Deep Autonomous Systems
Google Deep Mind has long been known for advanced research on artificial intelligence, especially Reinforcement Learning.
Deep is looking for ways to allow smart agents to learn autonomy and make decisions without human intervention. One of the most important uses of this research is the Agent AI that can help in areas such as health care.
Deep is developing agents that can process large volumes of medical data and perform predictive analysis. These technologies help health care providers provide more health care. In addition, Google is the creator of powerful Gemini models that contribute to the development of advanced artificial intelligence.
Antropic Claud (CLAUDE) Antropic Company
Anthropic Research Company has also introduced Claud 3.5 SONNET Factor; It is an advanced conversation factor that emphasizes safety, reliability and harmony with human values.
The cloud is designed to manage complex conversations, prioritize ethical guidance, and respond high quality for different types of tasks.
The anthropic approach is based on the development of a type of artificial intelligence systems that are both capable and designed to minimize potential prejudices and maintain a high level of transparency. Business owners can use the cloud to manage customer support and provide help in research and training.
Amazon Alexa Alexa
Amazon now uses Alexa’s infrastructure technology to create more advanced AI agents for commercial applications.
Organizations, through Amazon’s artificial intelligence agent called Alexa Plus, are implementing AI -activated AI agents to launch their business. These factors can take on tasks; Including the timing of meetings to order equipment.
By integrating Alexa Plus into business operations, Amazon has made it possible for employees to interact with systems in the moment. Such an approach has increased productivity.
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