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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