Connectivity graphs: a method for proving deadlock freedom based on separation logic

We introduce the notion of a connectivity graph —an abstract representation of the topology of concurrently interacting entities, which allows us to encapsulate generic principles of reasoning about deadlock freedom . Connectivity graphs are parametric in their vertices (representing entities like threads and channels) and their edges (representing references between entities) with labels (representing interaction protocols). We prove deadlock and memory leak freedom in the style of progress and preservation and use separation logic as a meta theoretic tool to treat connectivity graph edges and labels substructurally. To prove preservation locally, we distill generic separation logic rules for local graph transformations that preserve acyclicity of the connectivity graph. To prove global progress locally, we introduce a waiting induction principle for acyclic connectivity graphs. We mechanize our results in Coq, and instantiate our method with a higher-order binary session-typed language to obtain the first mechanized proof of deadlock and leak freedom.

Interaction Protocols for Multi-Robot Systems in Industry 4.0

In this chapter, the main methods of communication among multi-robot systems involved in Machine-to-Machine (M2M) applications, especially with regard the communication, reliability, stability and security among these robots, presenting various concepts through papers already published. A comparative study was carried out between two communication protocols applied in M2M technologies, the Queue Telemetry Transport (MQTT) developed by IBM along with Eurotech and the Constrained Application Protocol (CoAP). A study and survey of the characteristics of each of the protocols was carried out, as well as the method of operation of each of them and how both can be used in applications involving multiple robots. It was concluded that both protocols are considered ideal for use in in applications involving multi-robot systems. However, although the two protocols have been designed for application in environments with limited communication, the MQTT exchange protocol has advantages over CoAP, as a lower ovehead between message exchanges.

Diversity-sensitive social platforms and responsibility

There is an ongoing debate on how algorithms and machine learning can and should deal with human diversity while avoiding the pitfalls of statistical stereotyping, the re-enforcement of clichés and the perpetuation of unjust discrimination. Computer scientists try to tackle these issues by developing algorithms and social-interaction protocols for mediating diversity-aware interactions between people, for instance on diversity-sensitive social platforms. At the same time, diversity-related data often comprise sensitive personal data, and their collection, storage and management increases the vulnerability of users to various misuse scenarios. Already this observation leads to the question, how do we need to conceptualize responsibility to do justice to the increased vulnerability? In this paper, I thus focus on the questions a diversity-sensitive social platform raises with regard to responsibility, and propose a tentative ethical framework of responsibility for these platforms.

Studying human-AI collaboration protocols: the case of the Kasparov’s law in radiological double reading

Purpose The integration of Artificial Intelligence into medical practices has recently been advocated for the promise to bring increased efficiency and effectiveness to these practices. Nonetheless, little research has so far been aimed at understanding the best human-AI interaction protocols in collaborative tasks, even in currently more viable settings, like independent double-reading screening tasks. Methods To this aim, we report about a retrospective case–control study, involving 12 board-certified radiologists, in the detection of knee lesions by means of Magnetic Resonance Imaging, in which we simulated the serial combination of two Deep Learning models with humans in eight double-reading protocols. Inspired by the so-called Kasparov’s Laws, we investigate whether the combination of humans and AI models could achieve better performance than AI models alone, and whether weak reader, when supported by fit-for-use interaction protocols, could out-perform stronger readers. Results We discuss two main findings: groups of humans who perform significantly worse than a state-of-the-art AI can significantly outperform it if their judgements are aggregated by majority voting (in concordance with the first part of the Kasparov’s law); small ensembles of significantly weaker readers can significantly outperform teams of stronger readers, supported by the same computational tool, when the judgments of the former ones are combined within “fit-for-use” protocols (in concordance with the second part of the Kasparov’s law). Conclusion Our study shows that good interaction protocols can guarantee improved decision performance that easily surpasses the performance of individual agents, even of realistic super-human AI systems. This finding highlights the importance of focusing on how to guarantee better co-operation within human-AI teams, so to enable safer and more human sustainable care practices.

Compendious Study of Interaction Protocols in Multiagent Systems

The premise of the paper is to present a compendious study of interaction protocols pertaining to multiagent systems. Multiagent systems have evolved from the field of Distributed Artificial Intelligence and require numerous agents to cooperate and coordinate to cope with goal search. The primary ingredients to goal search are the language of communication and the interaction protocol. Agents in communication must be able to understand the language of communication and should also follow rules of interaction. The paper focuses on sharing understanding about various agent interaction protocols and it also discusses the promises and challenges each protocol offers to MAS research community.