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Exception handling has been successfully proposed in software engineering practice as a simple but effective technology to address abnormal situations possibly occurring at runtime. In this article, we present and explain the advantages of how exception handling can be seamlessly integrated in distributed systems—which are realized as multiagent systems—at an organizational level, by relying on the notion of responsibility.

Robustness is an important property of software systems; the availability of proper feedback is crucial to obtain it, especially when a system consists of distributed and interconnected components. Multiagent systems (MAS) are valuable for conceptualizing and implementing distributed systems, but they fall short in addressing robustness in a systematic way at design time. In this article, we provide a definition of accountability and show its use for designing robust MAS.

Accountability is often seen as a key notion in distributed systems, both in the human world and in software, on top of which interaction is built, together with the sibling notion of responsibility. However, there is limited support for the specification and use of such concepts in computational settings. This paper proposes an information model for computational accountability, which describes what data have to be available to allow, in any situation of interest arising from a group of interacting parties, the investigation and identification of accountability. The characterization of accountability provided by the model is grounded in the notions of just expectation and control. The information model is expressed in Object-Role Modeling (ORM), since it is well-suited to capture the relational nature of the accountability concept. An advantage of our model is that a designer can verify the consistency of a domain w.r.t. a set of accountability requirements. The paper exemplifies this checking by means of an Answer Set Program (ASP).

This work is set in the context of data-centric approaches and is motivated by the observation that business artifacts are not devised as natural means of coordination, despite the fact that they have this potential. Instead of using orchestration and choreography languages, we propose to enrich business artifacts with a normative layer that defines the coordination, basing our approach on social commitments. The straightforward advantage is an increased reusability of both processes and business artifacts, thanks to a clear decoupling between the coordination logic and the business logic. We show how social commitments can be leveraged for modularizing the design of distributed tasks and discuss the advantages of the approach from a software engineering perspective.

The paper describes Pietro Torasso’s contribution to the area of diagnostic problem solving, starting from the early 80’s and recalling the work carried on by Pietro and by the research group he started at the Department of Computer Science of the University of Torino.

This work proposes a notion of accountability for multi-agent systems, that supports the development of robust distributed systems. Accountability is grounded on responsibility, and encompasses both a normative dimension, and a structural dimension. For realizing robust distributed systems, conceived as agent systems or organizations, it is necessary to keep a right level of situational awareness, through the introduction of the means for gathering and propagating accounts, upon which actions can be taken. This paper presents a formalization of accountability, including the accountability lifecycle, for the design of robust agent organizations. Particular attention is given to the interplay of accountability and goals, by describing typical patterns in which accountability affects the state of an agent’s goals and vice versa. We illustrate the practical aspects of the proposal by means of JaCaMo (Boissier et al. Sci Comput Program 78(6):747–761, 2013. https://doi.org/10.1016/j.scico.2011.10.004).

Repairing a plan executed in a partially observable environment is a challenging task; especially when the plan to be repaired is part of a Multiagent Plan (MAP), and hence the synchronization among the agents further constrains the repair process. The paper formalizes a local plan repair strategy, where each agent in a MAP is responsible for controlling (monitoring and diagnosing) the actions it executes, and for autonomously repairing its own plan whenever an action failure is detected. The paper also describes how to mitigate the impact of an action failure on the plans of other agents when the local recovery strategy fails.