![]() We also introduce a mechanised sequential emulation procedure that encodes a high-level system specification into a sequential imperative program. As a consequence, stigmergies may capture the behaviour of several interesting classes of MASs in a compact and intuitive way. This diffusion happens transparently: the user of the language simply defines one or more stigmergic variables and assigns values to them. ![]() To bridge this gap, we put forward a high-level specification language for MASs, where agents operate on (parts of) a decentralised data structure, called a virtual stigmergy, which allows to model the influence of local changes on the global behaviour by asynchronously diffusing the knowledge of the agents. However, these languages often lack constructs to naturally capture distinctive features of MASs, and thus may be not appropriate for describing them. Meanwhile, formal verification research mainly targets low-level formalisms or traditional programming languages. Some existing MAS specification formalisms and platforms lack support for formal verification altogether, and are limited to simulation-based analysis others focus on specific sub-classes of MASs, or come with tailored verification platforms that might not keep up with the state of the art in formal verification. ![]() Because of this, formal verification of MASs is particularly challenging. This complexity stems from several distinctive features, such as nondeterministic individual behaviour and interactions, asynchronous communication, and a lack of central control. MASs feature an unprecedented degree of complexity, making their specification and analysis an open problem. MASs are a convenient modelling paradigm for complex scenarios across many research fields: they may either be used to describe and reason about existing systems (such as colonies of insects, social networks, economic markets), or to design and assess the correctness of new ones (such as swarms of robots, smart transportation systems). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones.Ī multi-agent system (MAS) is a collection of agents, often endowed with individual goals and a partial view of the whole system, that may be required to achieve complex goals by interacting with each other and with the environment. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI”-in particular, logic-based ones-will take place in the next few years. Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computer-scientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding.
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