Abstract. In open systems, i.e. systems operating in an environment that they cannot control and with components that may join or leave, behaviors can arise as side effects of intensive components interaction. Finding ways to understand and design these systems and, most of all, to model the interactions of their components, is a difficult but important endeavor. To tackle these issues, we present AbC , a calculus for attributebased 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.

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The notion of attribute-based communication seems promising to model and analyse systems with huge numbers of interacting components that dynamically adjust and combine their behaviour to achieve specific goals. A basic process calculus, named AbC, is introduced that has as primitive construct exactly attribute-based communication and its impact on the above mentioned kind of systems is considered. An AbC system consists of a set of parallel components each of which is equipped with a set of attributes. Communication takes place in a broadcast fashion and communication links among components are dynamically established by taking into account interdependences determined by predicates over attributes. First, the syntax and the reduction semantics of AbC are presented, then its expressiveness and effectiveness is demonstrated by modelling two scenarios from the realm of TV streaming channels. An example of how well-established process calculi could be encoded into AbC is given by considering the translation into AbC of a prototypical π-calculus process

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Collective-adaptive systems offer an interesting notion of interaction where run-time contextual data are the driving force for interaction. The attribute-based interaction has been proposed as a foundational theoretical framework to model CAS interactions. The framework permits a group of partners to interact by considering their run-time properties and their environment. In this paper, we lay the basis for an efficient, correct, and distributed implementation of the attribute-based interaction framework. First, we present three coordination infrastructures for message exchange, then we prove their correctness, and finally we model them in terms of stochastic processes to evaluate their performance.

We propose a formalism to model and reason about reconfigurable multi-agent systems. In our formalism, agents interact and communicate in different modes so that they can pursue joint tasks; agents may dynamically synchronize, exchange data, adapt their behaviour, and reconfigure their communication interfaces. Inspired by existing multi-robot systems, we represent a system as a set of agents (each with local state), executing independently and only influence each other by means of message exchange. Agents are able to sense their local states and partially their surroundings. We extend ltl to be able to reason explicitly about the intentions of agents in the interaction and their communication protocols. We also study the complexity of satisfiability and model-checking of this extension.

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