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Résumé : This chapter provides an introduction to the multi-agent coordination by reinforcement learning (RL) and evolutionary algorithms. It also provides a thorough survey of the existing literature of RL with a brief overview of evolutionary optimization (EO) to examine the role of the algorithms in the context of multi-agent coordination. The chapter includes the classification of multi-agent coordination based on different criterion, such as the level of cooperation, knowledge sharing, communication, and the like. It also includes multi-robot coordination employing EO, and specially RL for cooperative, competitive, and their composition for application to static and dynamic games. The chapter describes the single agent planning terminologies and algorithms. It deals with an overview of the metrics used to compare the performance of the algorithms in coordination.