EAN: 9783031004155

SYNTHESIS LECTURES ON ARTIFICIAL INTELLIGENCE A...

Multiagent systems is an expanding field that blends classical fields like game theory and
decentralized control with modern fields like computer science and machine learning. This
monograph provides a concise introduction to the subject  covering the theoretical foundations
as well as more recent developments in a coherent and readable manner. The text is centered on
the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of
multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under
uncertainty. Chapter 3 is a brief introduction to game theory  explaining classical concepts
like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of
collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making
under partial observability. Chapter 6 focuses on the design of protocols that are stable
against manipulations by self-interested agents. Chapter 7 provides a short introduction to the
rapidly expanding field of multiagent reinforcement learning. The material can be used for
teaching a half-semester course on multiagent systems covering  roughly  one chapter per
lecture.

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