290 research outputs found

    A synergistic and extensible framework for multi-agent system verification

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    Recently there has been a proliferation of tools and languages for modeling multi-agent systems (MAS). Verification tools, correspondingly, have been developed to check properties of these systems. Most MAS verification tools, however, have their own input language and often specialize in one verification technology, or only support checking a specific type of property. In this work we present an extensible framework that leverages mainstream verification tools to successfully reason about various types of properties. We describe the verification of models specified in the Brahms agent modeling language to demonstrate the feasibility of our approach. We chose Brahms because it is used to model real instances of interactions between pilots, air-traffic controllers, and automated systems at NASA. Our framework takes as input a Brahms model along with a Java implementation of its semantics. We then use Java PathFinder to explore all possible behaviors of the model and, also, produce a generalized intermediate representation that encodes these behaviors. The intermediate representation is automatically transformed to the input language of mainstream model checkers, including PRISM, SPIN, and NuSMV allowing us to check different types of properties. We validate our approach on a model that contains key elements from the Air France Flight 447 acciden

    Using Formal Methods for Autonomous Systems: Five Recipes for Formal Verification

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    Formal Methods are mathematically-based techniques for software design and engineering, which enable the unambiguous description of and reasoning about a system's behaviour. Autonomous systems use software to make decisions without human control, are often embedded in a robotic system, are often safety-critical, and are increasingly being introduced into everyday settings. Autonomous systems need robust development and verification methods, but formal methods practitioners are often asked: Why use Formal Methods for Autonomous Systems? To answer this question, this position paper describes five recipes for formally verifying aspects of an autonomous system, collected from the literature. The recipes are examples of how Formal Methods can be an effective tool for the development and verification of autonomous systems. During design, they enable unambiguous description of requirements; in development, formal specifications can be verified against requirements; software components may be synthesised from verified specifications; and behaviour can be monitored at runtime and compared to its original specification. Modern Formal Methods often include highly automated tool support, which enables exhaustive checking of a system's state space. This paper argues that Formal Methods are a powerful tool for the repertoire of development techniques for safe autonomous systems, alongside other robust software engineering techniques.Comment: Accepted at Journal of Risk and Reliabilit

    Plan Library Reconfigurability in BDI Agents

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    One of the major advantages of modular architectures in robotic systems is the ability to add or replace nodes, without needing to rearrange the whole system. In this type of system, autonomous agents can aid in the decision making and high-level control of the robot. However, when autonomously replacing a node it can be difficult to reconfigure plans in the agent's plan library while retaining correctness. In this paper, we exploit the formal concept of capabilities in Belief-Desire-Intention agents and describe how agents can reason about these capabilities in order to reconfigure their plan library while retaining overall correctness constraints. To validate our approach, we show the implementation of our framework and an experiment using a practical example in the Mars rover scenario

    An architectural framework for self-configuration and self-improvement at runtime

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    Multi-Agent Systems

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    This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019
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