Heartbeat synchronization, where agents emit short, periodic, near-simultaneous flashes, is achieved as an emergent behavior of the multi-agent system through a novel decentralized protocol. The proposed protocol operates in large multi-agent systems without requiring agents to share a global frequency or phase. Agents interact iteratively with randomly selected peers, pausing for a random interval before triggering each interaction. Starting from random states, agents update their states through pairwise interactions and continuously emit light when their state meets a condition. Two emergent properties of these flashes are studied: the flash period, which is the interval between consecutive flashes, and the flash duration, which is the duration of each flash. Experiments conducted using a custom-built simulator provide strong empirical evidence that the protocol induces a sufficiently regular flash period and a sufficiently short flash duration to enable effective heartbeat synchronization in real-world applications.

The growing adoption of artificial intelligence in business processes is profoundly changing collaboration practices, knowledge management and value creation. This paper offers a critical review of recent literature on this topic, with particular attention to the context of collaborative enterprises. Through a comparative analysis of four recent contributions on this topic, this paper highlights that the effectiveness of artificial intelligence in the context of collaborative enterprises depends not only on the technology itself, but also on the integration within organizational environments characterized by advanced collaboration and knowledge management practices. The paper provides an interpretation of collaborative enterprises as socio-technical ecosystems, in which artificial intelligence becomes a force that promotes innovation, but only if it is embedded in a culture of co-design and continuous learning. The surveyed findings offer valuable insights for rethinking organizational models and promoting a more conscious and synergistic adoption of artificial intelligence technologies in collaborative enterprises.

The scenarios considered in this paper are examples of indoor positioning problems in industrial premises like warehouses and storage buildings. As usual in these cases, some anchor nodes are deployed at fixed and known locations near the ceiling of the considered environment to support maximum coverage and minimum interference positioning. These scenarios are critical for ordinary positioning algorithms because of the symmetries introduced by the deployment of the anchor nodes, and therefore alternative algorithms based on optimization are required. The whale optimization algorithm is considered in this paper as a viable alternative to support accurate positioning in the considered scenarios. The reported experimental campaign is designed to assess the performance of this algorithm for 2D positioning using two options to reduce the positioning problem from 3D to 2D under the assumption that ultra-wide band ranging is used to estimate distances. The first option treats the problem as genuinely 3D. The second option projects the estimated distances on the target plane to work in 2D. The results of the reported experimental campaign provide empirical evidence that the whale optimization algorithm can be effectively used for accurate 2D positioning using both options, but the second option is preferable because it requires a lower computational cost.

This volume contains a selection of the papers presented at the |$36^{\textrm {th}}$|Italian Conference on Computational Logic (CILC 2021), held on September |$7^{\textrm {th}}$|–|$9^{\textrm {th}}$|⁠, |$2021$| in Parma, Italy. The Italian Conference on Computational Logic is the annual conference organized by the Group of researchers and Users of Logic Programming (GULP, www.programmazionelogica.it). Since the first event of the series, which took place in Genoa in |$1986$|⁠, the annual GULP conference represents a major opportunity for researchers and practitioners interested in computational logic to meet and exchange ideas. Furthermore, over the years, the conference broadened its horizons from logic programming to include related topics, such as declarative programming, formal verification of systems, knowledge representation, deductive databases and a wide range of applications in the broader area of Artificial Intelligence. The annual GULP conference is a traditional event of the Italian community of researchers and practitioners interested in logic programming, but its scope has become more and more international over the years. Despite the very peculiar situation caused by the COVID-19 pandemic, the community significantly responded to the call, thus allowing the technical program of CILC |$2021$| to feature |$23$| presentations of high-quality papers, of which |$19$| were original papers. This volume of the Journal of Logic and Computation contains extended and revised versions of a selection of the papers presented at CILC |$2021$|⁠. As a result of an additional review process, during which each submission was reviewed by three referees, |$8$| papers were accepted to be included in this volume. Accepted contributions range from foundations and theoretical results to practical experiences, case studies and applications. They cover a wide range of relevant topics related to computational logic in the broad sense, including agents and multi-agent systems, logic programming, runtime verification and healthcare. In the following, the featured papers are briefly summarized.

The 19thedition of the “Adaptive Computing (and Agents) for Enhanced Collaboration” (ACEC) track at WETICE 2021 targets the relevant topic of adaptation in relation to tools, methods and techniques for the enterprise. The aim of the track is to bring together researches and practitioners, working on agentbased software systems and/or adaptive computing, to present results and discuss innovative ideas. This report outlines the content of the papers accepted for presentation at the track.

The 17th edition of the "Adaptive Computing (and Agents) for Enhanced Collaboration" (ACEC) track at WETICE 2019 focuses mostly on the area of adaptive agent-based techniques for the enterprise. The aim of the track is to bring together researches and practitioners from the fields of software agents and adaptive computing to present results and discuss innovative ideas. This report outlines the content of papers accepted for presentation at the track.

This paper studies analytically the dynamics of the opinion in multi-agent systems when only the sociological phenomenon known as diffusion is considered.First, the paper recalls a framework for the analytic study of opinion dynamics which has been already applied to describe the effects of a number of sociological phenomena.Then, the framework is specialized to the study of diffusion, according to which the opinion of an agent can be influenced by the social context.Diffusion is introduced in the framework by stating stochastic rules meant to describe at the microscopic level how diffusion contributes to change the opinion of an agent.The obtained model is used to derive collective and asymptotic properties of multi-agent systems when only diffusion is considered, which are verified against specific simulations shown in the last part of the paper.The paper is concluded with a recapitulation of presented results and an outline of future work.

The 16th edition of the "Adaptive Computing (and Agents) for Enhanced Collaboration" (ACEC) track at WETICE 2018 focuses mostly on the area of adaptive agent-based techniques for the enterprise. The objective of the track is to bring together researches from the fields of software agents and adaptive computing to present results and discuss in the context of adaptive techniques and enterprise collaboration. This report briefly reports on the content of accepted papers.

This paper introduces an instantiation of the constraint logic programming scheme called CLP(PolyFD) in which variables take values from finite subsets of the integers and constraints are expressed as equalities, inequalities, and disequalities of polynomials with integer coefficients. Such constra ints, which we call polynomial constraints over finite domains, can be treated effectively by means of a specific solver under the assumption that initial approximations of the domains of variables are available. The proposed solver deals with constraints in a canonical form and it uses the modified Bernstein form of polynomials to detect the satisfiability of constraints. The solver is complete and a preliminary assessment of its performance is reported.

In this paper, a comparison between the pseudocode of a well-known algorithm for solving distributed constraint satisfaction problems and the implementation of such an algorithm in JADEL is given.First, background and motivations behind JADEL development are illustrated.Then, we make a description of the problem and a brief introduction to JADEL.The core of this work consists in the translation of the algorithm pseudocode in JADEL code, which is described in details.Scope of the paper is to evaluate such a translation, in terms of closeness to pseudocode, complexity, amount of code written and performance.

The 15th edition of the "Adaptive Computing (and Agents) for Enhanced Collaboration" track at WETICE 2017 focuses on the areas of adaptive agent-based services and adaptive techniques for enterprises. The purpose of the track is to bring together researches in the fields of software agents and adaptive computing as they relate to the context of adaptive techniques and enterprise collaboration. This report briefly discusses the content of the papers accepted for presentation in the track.

This report describes the culmination of the 13th installment of the “Adaptive Computing (and Agents) for Enhanced Collaboration” (ACEC) track. ACEC focuses on collaborative computing that occurs dynamically among Web-accessible software systems and devices. The articulation of these network artifacts must be controlled by adaptive, intelligent control mechanisms, sometimes realized as agents. ACEC has for over 13 years brought together researchers from multiple disciplines to address the challenges associated with effective, just-in-time collaboration. The track this year showcases papers that explore emerging models and design patterns for adaptive architectures for a varied set of domains such as robotic and crowdsourcing.

JSetL is a Java library that endows Java with a number of facilities that are intended to support declarative and constraint (logic) programming. In this paper we show how JSetL can be used to support general forms of nondeterministic programming in

This paper summarizes the current state of development of JADEL, a novel programming language that eases the implementation of agents and multi-agent systems. First, the introduction of a novel agent programming language is motivated and the approach that was used to design JADEL is presented. Then, the characteristic features of JADEL are described by means of a didactic example. The paper is concluded with a short discussion about current and planned developments of JADEL.

Multi-agent systems have been contributing to the development of both theory and practice of complex distributed systems. Social networks are probably the systems that exhibit the highest degree of similarity with multi-agent systems because members of a social network interact as agents do in a multi-agent system. Multi-agent system may be the best solution to enrich and facilitate the interaction and the collaboration among the members of a social network. After an introduction on the relationships between multi-agent systems and social networks, this paper describes Blogracy, a multi-agent system that supports the interaction among the members of a social network.

This paper summarizes a constraint solving technique that is used to reason effectively in the scope of a set-based constraint language that supersedes existing finite domain languages. The first part of this paper motivates the presented work and introduces the constraint language, namely the language of Hereditarily Finite Sets (HFS). Then, the proposed constraint solver is detailed in terms of a set of rewrite rules that exploit finite domain reasoning within the HFS language. The proposed solution improves previous work on CLP (SET) [11] by integrating intervals into the constraint system and by providing a new layered architecture for the solver that supports more effective constraint solving strategies. On the other hand, the proposed approach provides enhanced expressivity and flexibility of domain representation than those usually found in existing finite domain constraint solvers.

This paper describes two versions of a novel approach to developing binary classifiers, based on two evolutionary computation paradigms: cellular programming and genetic programming. Such an approach achieves high computation efficiency both during evolution and at runtime. Evolution speed is optimized by allowing multiple solutions to be computed in parallel. Runtime performance is optimized explicitly using parallel computation in the case of cellular programming or implicitly taking advantage of the intrinsic parallelism of bitwise operators on standard sequential architectures in the case of genetic programming. The approach was tested on a digit recognition problem and compared with a reference classifier.

Ubiquity is one of the most important keyword of the next generation software systems. We want our systems to follow users wherever they go, and we want our systems to extend their reach to the telephony world and to its base of several hundred million users. The ever-increasing diffusion of handy appliances, e.g. palmtops and cellular phones, is familiarizing people with the use of computers for their everyday job and, more impressively, for their everyday life. This suggests that the market of software systems for mobile applications will increase dramatically in the near future.

Software engineering relies on the possibility of describing a system at different levels of abstraction. Agent-oriented software engineering introduces a new level of abstraction, that we called agent level, to allow the architect modelling a system in terms of interacting agents. This level of abstraction is not supported by an accepted set of tools and notations yet, even if a number of proposals are available. This paper introduces: (i) An UML-based notation capable of modelling a system at the agent level and (ii) A development framework, called ParADE, exploiting such a notation. The notation we propose is formalized in terms of a UML profile and it supports the realisation of artefacts modelling two basic concepts of the agent level, i.e., the architecture of the multi-agent system and the ontology followed by agents. The choice of formalising our notation in terms of a UML profile allows using it with any off-the-shelf CASE tool. The ParADE framework takes advantage of this choice by providing a code generator capable of producing skeletons of FIPA-compliant agents from XMI files of agent-oriented models. The developer is requested to complete the generated skeletons exploiting the services that ParADE and the underlying agent platform provide.

This paper presents a cooperative platform that allows the sharing of information as well as the interactive use of different kinds of application in a synchronous mode. The access to the collaborative sessions is possible from different kinds of terminal and network (fixed or mobile). In particular, we address Web users and mobile users with sufficient bandwidth. The platform is based on the centralised sharing of an off-the-shelf application that relies on a collaborative version of the graphics libraries used in Java and Microsoft Windows. A first prototype of the platform has been experimented by Ph.D. students during a seminar distributed across Italy.