Fetch.ai is an interchain protocol that operates as a Layer 1 blockchain, utilizing Cosmos SDK and Multi-Agent System principles. Its goal is to establish a decentralized infrastructure for P2P applications that are capable of automation and AI functionalities.
The network functions through a group of independent agents that interact via the blockchain to complete their tasks. To provide developers with tools for building and running these agents, the Fetch.ai team created the Autonomous Economic Agent (AEA) framework.
In addition to the AEA framework, the team has launched two groundbreaking platforms. CoLearn, a marketplace for data and AI models, allows users to monetize their data and AI models. DabbaFlow, a decentralized data-sharing protocol, allows users to securely share their data across multiple parties without a middleman.
The FET token serves as the native token for the Fetch.ai ecosystem. The team boasts an impressive research team, continually developing innovative solutions for the platform’s advancement.
Overall, Fetch.ai is an exciting project at the forefront of decentralized P2P applications with AI capabilities. Their achievements to date demonstrate their commitment to creating a more innovative and interconnected digital world.
Fetch.ai is an interchain protocol, built using the Cosmos SDK
Built using principles of the Multi-Agent system, branch of AI
Mission is to build infrastructure for decentralized P2P applications
Fetch Wallet
Forked from Kepler wallet
Store and stake FET
Mobile and PC version
FET token is the native token for the Fetch.ai ecosystem
Network fees
Staking
Autonomous machine-to-machine ecosystem
Network agents work as independent parties and interact via the blockchain network
To perform their tasks, agents connect and negotiate with each other
Agreements made between the agents are recorded on the blockchain network
Rewards to stakeholders who contribute to the federated learning models
CoLearn Marketplace
DabbaFlow
Decentralized data-sharing protocol
Mainnet launched
Autonomous Economic Agent (AEA) framework is a development suite that equips you with an efficient and accessible set of tools for building and running AEAs. It is modular and composable
ACN helps agents interact over the internet
CoLearn
A library that enables privacy-preserving decentralized ML tasks
A marketplace for data and AI models
A Blockchain mediated collective learning system
DabbaFlow
Provides privacy to Colearn
Data sharing platform
Jenesis
CL tool for rapid contract and service development
Axim
Helps you make informed decisions and reach your goal
Optimizes business functions
Agents Based Modelling (ABM)
An agent is a piece of software that represents an entity (individual, organization, or object) and acts continuously and autonomously (with limited or no interference) on its behalf.
Key characteristics
Representation
Autonomy
Self-interest
Proactive
Reactive
ABM consists of a system of agents and connections between them
Multi-Agents Systems (MAS)
Group of agents that interact with each other and the environment to achieve specific goals
Key characteristics
Decentralization
Heterogeneity
Scalability
Robustness
Adaptability
Highly complex and difficult to predict
Building since 4 years
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