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 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.

Wireless Sensor Networks (WSNs) consist of a collection of spatially distributed radio transceivers with attached sensors that can measure and gather information from the environment. In this paper, we focus on the application of WSNs to indoor localization and, for this purpose, we propose the use of a Ultra Wide Band (UWB) WSN. The use of UWB signals guarantees robust performance in dense multipath environments, making them an attractive choice for indoor localization. In this paper, we discuss on different localization strategies: first classic geometric approaches are considered, then the mathematical framework is re-interpreted as an optimization problem. In the latter context, we propose the use of Particle Swarm Optimization (PSO) in particular, which can overcome limitations of classic (geometric) approaches.

In this paper, we consider the problem of locating an Automated Guided Vehicle (AGV) which moves on a plane in an industrial environment by means of Ultra-Wide Band (UWB) signaling from fixed Anchors Nodes (ANs) situated in the (three-dimensional) space. An analytical approach to optimize, under proper (realistic) constraints, the placement of the ANs used to locate the AGV is proposed. Analytical results are confirmed by simulations.