In open systems exhibiting adaptation, behaviors can arise as side effects of intensive components interaction. Finding ways to understand and design these systems, is a difficult but important endeavor. To tackle these issues, we present AbC, a calculus for attribute-based communication. An AbC system consists of a set of parallel agents each of which is equipped with a set of attributes. Communication takes place in an implicit multicast fashion, and interactions among agents are dynamically established by taking into account “connections” as determined by predicates over the attributes of agents. First, the syntax and the semantics of the calculus are presented, then expressiveness and effectiveness of AbC are demonstrated both in terms of modeling scenarios featuring collaboration, reconfiguration, and adaptation and of the possibility of encoding channel-based interactions and other interaction patterns. Behavioral equivalences for AbC are introduced for establishing formal relationships between different descriptions of the same system.