Decentralized Economic Systems: Incentives & Blockchain Applications

Description

This lecture by the instructor covers the concept of decentralized economic systems, focusing on distributed resource allocation and federated learning. It delves into the challenges of traditional centralized allocation methods, such as spectrum wastage, and introduces decentralized solutions using blockchain technology. The discussion extends to federated learning systems, exploring the design of incentives to encourage desired behavior in distributed agents. Practical implementations like Quai.Network and HashAuctions are presented, showcasing how blockchain applications can revolutionize economic systems. The lecture emphasizes the importance of well-designed incentives and tokenomics in achieving decentralized decision-making and efficient resource allocation.

Official source

https://mediaspace.epfl.ch/media/0_ow6g0t4c

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Related concepts (41)

Distributed artificial intelligence

Distributed Artificial Intelligence (DAI) also called Decentralized Artificial Intelligence is a subfield of artificial intelligence research dedicated to the development of distributed solutions for problems. DAI is closely related to and a predecessor of the field of multi-agent systems. Multi-agent systems and distributed problem solving are the two main DAI approaches. There are numerous applications and tools. Distributed Artificial Intelligence (DAI) is an approach to solving complex learning, planning, and decision-making problems.

Software agent

In computer science, a software agent or software AI is a computer program that acts for a user or other program in a relationship of agency, which derives from the Latin agere (to do): an agreement to act on one's behalf. Such "action on behalf of" implies the authority to decide which, if any, action is appropriate. Some agents are colloquially known as bots, from robot. They may be embodied, as when execution is paired with a robot body, or as software such as a chatbot executing on a phone (e.g.

Multi-agent system

A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents. Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. Intelligence may include methodic, functional, procedural approaches, algorithmic search or reinforcement learning. Despite considerable overlap, a multi-agent system is not always the same as an agent-based model (ABM).

Machine learning

Machine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.

Spectrum management

Spectrum management is the process of regulating the use of radio frequencies to promote efficient use and gain a net social benefit. The term radio spectrum typically refers to the full frequency range from 1 Hz to 3000 GHz (3 THz) that may be used for wireless communication. Increasing demand for services such as mobile telephones and many others has required changes in the philosophy of spectrum management. Demand for wireless broadband has soared due to technological innovation, such as 3G and 4G mobile services, and the rapid expansion of wireless internet services.