Summary

A Multi-Agent System (MAS) refers to a network of agents functioning collectively, often in a decentralized manner, to achieve a set of objectives. These agents can interact with each other and with their environment, each following their own set of rules or strategies.

ELI5

Imagine a group of robots working together in a factory. Each robot knows its job - one may assemble pieces, another may paint, and another may check quality. They all work separately, but together they’re able to build a car. This is similar to a Multi-Agent System - it’s like a team of smart computers, each with their own role, all working together to solve a problem.

In-depth explanation

In the field of Artificial Intelligence (AI), a Multi-Agent System (MAS) constitutes a set of autonomous agents designed to solve complex problems or carry out tasks. Each agent in the MAS possesses a degree of autonomy and can perceive its environment, make decisions, and take actions based on its pre-defined set of rules.

MAS can be characterized by their degree of cooperation, ranging from competitive to cooperative. In competitive MAS, the agents pursue their goals independently and might even work against each other. In cooperative MAS, the agents collaborate and share the knowledge to achieve a common goal. There might also be instances where agents display both cooperation and competition, which is called co-opetition.

An agent’s decision-making process is determined by its pre-defined rules or strategies, which would, in turn, depend on the agent’s goal, its current perception of the environment, and the state of other agents. For example, in a game of chess each piece (an agent) has a certain way it can move (its rules), and the objective (reaching checkmate) is determined by the positions and states of both friendly and opponent pieces.

A number of key AI technologies come into play in MAS including Machine Learning, Genetic Algorithms, and Swarm Intelligence. Each of these technologies can help optimize the interactions, strategies, and learning processes of agents within the system.

Agent, Autonomous Systems, Distributed Artificial Intelligence, Genetic Algorithms, Machine Learning (ML),, Swarm Intelligence.