This chapter examines the representational and algorithmic aspects of a class of graph-theoretic models for multiplayer games, known broadly as graphical games, that specify restrictions on the direct payoff influences among the player population.
In this chapter we examine the representational and algorithmic aspects of a class of graph-theoretic models for multiplayer games. Known broadly as graphical games, these models specify restrictions on the direct payoff influences among the player population. In addition to a number of nice computational properties, these models have close connections to well-studied graphical models for probabilistic inference in machine learning and statistics.