What Are AI Agents? Definition, Types, and Examples

AI Agents, also known as Agentic AI, are the latest wave of artificial intelligence programs to enter the industry. These programs possess the ability to perform tasks autonomously and independently, relying on their own knowledge.

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Imagine using these programs to autonomously execute cryptocurrency transactions on decentralized exchanges, manage wallets, and integrate with smart contracts. Is it scary? Perhaps, but it is also highly practical. Artificial intelligence has revolutionized the way we live and interact. In this article, we will explore what AI Agents are, how they work, and their applications in the blockchain and cryptocurrency space. We will also introduce some of the best AI Agent projects and examine how they differ from AI assistants like Alexa and chatbots like ChatGPT.

What Are AI Agents?

An AI Agent, or Agentic AI, is an autonomous AI program that can plan, learn from experiences, adapt to new information in the real world, and make decisions based on the tasks and responsibilities assigned to it.

These programs improve themselves through feedback and use advanced algorithms and sensors to perform tasks and interact with their environment.

Key Features of Powerful AI Agents

According to Lilian Weng, Head of Safety Systems at OpenAI, a good AI agent should possess the following characteristics and capabilities:

Planning:
An AI agent should be able to generate a step-by-step plan with specific goals through a prompt (written instruction) and learn from its mistakes through a reward system to improve its subsequent outputs.
Memory:
AI agents should be able to use their short-term memory to process chat-based prompts and conversations, and alongside this, they should be able to track subsequent requests by maintaining and retrieving long-term data.
Tool Use:
An AI agent should be able to query APIs to request additional information or perform an operation based on what the end-user has requested.

How Do AI Agents Differ from AI Assistants and Chatbots?

There is often confusion about the differences between AI agents, AI assistants, and chatbots, as their functions appear to be similar at first glance. In this section, we will explore the fundamental differences between these two types.

Learning and Adaptation: What sets AI agents apart from AI assistants and chatbots like ChatGPT is their ability to continuously improve through machine learning and adapt to new conditions.

These programs are designed to analyze data, predict outcomes, and adjust their behavior without human intervention or supervision. This feature allows them to make smarter and more optimal decisions.

Autonomy: Unlike chatbots or virtual assistants like Alexa, AI agents do not just follow predefined rules. These agents are programs that can autonomously perform tasks on behalf of their users.

They are designed to analyze their surroundings and make decisions, operating independently to achieve their set goals. In other words, the high level of autonomy of these programs, which eliminates the need for direct human intervention and user involvement, is the reason for the difference between AI agents and traditional robots.

How Do AI Agents Work?

The operation of AI agents involves three stages: data collection, decision-making, and execution. This process allows the agent to operate autonomously, adapt to its environment, and perform optimally.

Data Collection: AI agents use sensors, APIs, or input mechanisms to collect data from their surroundings. For example, these programs can collect data on price or transaction volume in the market or user behavior data within an application.

Therefore, the collection of raw data for processing is the first step in the work of an AI agent.

Analysis and Decision-Making: After processing the data through machine learning algorithms and predictive models, AI agents evaluate the options available based on their goals.

These programs have the ability to predict trends, optimize strategies, or make efficient trading decisions in complex environments.

Execution and Adaptation: In the final stage, AI agents execute operations such as executing trades, managing portfolios, or interacting with decentralized platforms. At this stage, these programs learn from the feedback they receive and adjust their strategies to improve effectiveness. This helps them adapt to rapid changes in the work environment.

AI Agents in the Crypto and Digital Currency Space

In the blockchain and cryptocurrency space, AI agents are autonomous software programs designed to perform complex tasks on blockchain networks with minimal human intervention.

These programs are used to analyze data, make decisions, and execute processes such as trading, asset management, interacting with decentralized finance platforms, or even posting on social media platforms like Twitter. By analyzing massive datasets, these programs identify trends and optimize strategies, improving performance while reducing risks.

However, the application of AI agents in the crypto space is not limited to these areas; these programs have been developed in fields such as creative art, NFT creation, and the management of Decentralized Autonomous Organizations (DAOs), contributing to the expansion of the digital ecosystem.

The Evolution of AI Agents in Digital Currencies

The path of AI agent evolution in the crypto world began with simple automation tools and has now reached intelligent systems capable of transforming decentralized platforms.

Stage 1: Initial Automation

Initially, AI agents only executed pre-programmed tasks such as trading based on fixed parameters. Although these bots were efficient, they lacked adaptability.

Stage 2: Integration with Blockchain

Following the bots, innovations such as Coinbase’s AI agent, Based, brought autonomous on-chain capabilities like NFT creation and automatic token transfers.

Stage 3: Advanced Intelligence

Modern AI agents like Truth Terminal use machine learning and the latest AI models to autonomously execute tasks such as creating a “new community” in the meme coin market.

These advancements show that AI agents have evolved from static tools to dynamic systems, revolutionizing the possibilities in crypto markets. The meme coin GOAT is one such example, which we will discuss in more detail later.

Benefits and Applications of AI Agents in the Cryptocurrency Space

AI agents are transforming the crypto ecosystem through their ability to automate, analyze, and innovate. The advantages and applications of these programs in the blockchain space include the following:

1. Automated Tasks in DeFi

In the DeFi space, managing transactions, optimizing returns, or even understanding risks is a very difficult and time-consuming task for traders, especially newcomers. Therefore, AI agents can monitor the market and execute activities such as yield farming, liquidity allocation, and trading strategies.

These programs can also act as your representative in DAOs, participating in voting or proposing proposals on your behalf.

For example, an agent can monitor 50 liquidity pools simultaneously and allocate your capital to the most suitable pools by maximizing returns and minimizing human intervention.

2. Art and Music Production

AI agent programs can produce unique digital art and dynamic NFTs that evolve through user interaction.

For example, the Zerebro AI system is one of the agents that, alongside NFT collections, has also produced two music albums on Spotify in this way.

3. Content Creation and Management

AI agents can be used as an influencer for content creation and even interacting with fans. For example, Luna, an agent launched on the Virtuals Protocol, is a virtual model on TikTok with over 500,000 followers and is live-streaming 24/7.

AIXBT is another AI agent launched on the Virtuals Protocol. This agent, by following more than 400 influencers on Twitter, instantly reviews events and automates the data interpretation process.

4. Trading and In-Chain Data Analysis

AI agents are excellent options for identifying arbitrage opportunities. These programs can analyze market trends and the tokenomics of digital currencies and suggest promising projects for investment.

For example, VaderAI aims to become one of the leading AI agents in the field of asset management.

4. Simplifying Payments

Traditional systems such as credit cards or payment processors are not suitable for managing micro or multiple transactions. Cryptocurrencies have solved this problem with their low fees and fast transactions. In this case, an AI agent can use crypto systems for fast and pre-determined payments on behalf of the user. For example, an AI agent can pay on behalf of you for accessing weather or news data.

Types of AI Agents

AI agents come in various types, from single-purpose agents to advanced learning programs, each with its own strengths and weaknesses. As this field continues to evolve, new types of AI agents are likely to emerge in the future. In this section, we will explore the different models of AI agents.

1. Reflex Agents

These agents use a Model of the World (MOTW) for decision-making. MOTW is an internalized model of the outside world that is used to understand the surroundings and the reality of our world. This type of agent can recall some past states and make decisions based on current and past experiences.

Tools like ESLint or Pylint, which use predefined rules to evaluate code, are of this type. Linting is a process where you can identify errors in the code.

2. Goal-Based Agents

This type of agent uses specified knowledge and a goal (or prompt) to achieve specific objectives. Advanced integrated development environments equipped with AI code, such as GitHub Copilot, are of this type.

3. Utility-Based Agents

The nature of this type of agent is to achieve a goal in the best possible way. The best possible way is determined by evaluating various possible approaches.

Tools that rank and allocate bugs based on severity, impact, and developer load are of this type.

4. Learning Agents

This model of agent improves its performance over time by learning from its experiences. These programs contain learning elements that, depending on user feedback and a performance element that uses the acquired knowledge, improve the outputs.

Code completion tools like GitHub Copilot, which improve over time, are of this type.

The Future of AI Agents in Digital Currencies

Although we are still in the early stages of using AI agents in the blockchain, the potential of this technology is so great that it can revolutionize the life of humanity.

Brian Armstrong, CEO of Coinbase, has been one of the major proponents of using AI agents in the crypto space and has even stated that the future of blockchain transactions may become more dependent on these automated entities every day.

In the following, we will discuss the various aspects of the impact of these programs:

AI-Based Decentralized Economies

Imagine a network of interactive AI agents, each performing their own specialized tasks. These agents can interact with each other to create a self-sufficient economy in which the agents themselves exchange assets and autonomously manage resources.

Widespread Adoption of Web 3

By automating and simplifying blockchain interactions, AI agents can make Web 3 technologies accessible to everyone, from tech enthusiasts to ordinary users.

Advanced DeFi Applications

With the further development of AI tools, new strategies for optimizing returns, managing risk, and even collective investment may be provided.

Conclusion

AI agents, with their ability to automate tasks, make smarter decisions, and simplify complex systems, are helping to expand the boundaries in the digital economy. AI agents are autonomous and independent programs that can perform tasks on behalf of the user with minimal human intervention. One of the current main applications of AI agents in the crypto and blockchain space is. In this space, an AI agent can be used to automate the execution of transactions, interact with smart contracts, create NFT tokens, produce music and content, and many other things.

Frequently Asked Questions

1. What Are AI Agents?

An AI agent, or agentic AI, is an autonomous and independent AI program based on artificial intelligence that has the ability to plan, learn from experiences, adapt to new information in the real world, and make decisions based on the tasks and responsibilities assigned to it.

2. What Are the Best AI Agent Projects?

Truth Terminal, Zerebro, AIXBT, Fetch.ai, SingularityNET, and others are some of the best AI agents in the field of digital currencies.

3. Are AI Agents Safe?

Security vulnerabilities are an important aspect of the development and use of AI agents, and if they are defective or penetrated, it can have a very significant impact on their outputs.