On emergent complex behaviour, self-organised criticality and phase transitions in multi-agent systems: autonomy oriented computing (AOC) perspectives

Jamming transition of high-dimensional traffic dynamics

A social network is composed of social individuals and their relationships. In many real-world applications, such a network will evolve dynamically over time and events. A social network can be naturally viewed as a multiagent system if considering locally-interacting social individuals as autonomous agents. In this paper, we present an Autonomy-Oriented Computing (AOC) based model of a social network, and study the dynamics of the network based on this model. In the AOC model, the profile of agents, service-based interactions, and the evolution of the network are defined, and the autonomy of the agents is emphasized. The model can reveal dynamic relationships among global performance, local interaction (partner selection) strategies, and network topology. The experimental results show that the agent network forms a community with a high clustering coefficient, and the performance of the network is dynamically changing along with the formation of the network and the local interaction strategies of the agents. In this paper, the performance and topology of the agent network are analyzed, and the factors that affect the performance and evolution of the agent network are examined.

Generative design for complex floorplans in high-rise residential buildings: A Monte Carlo tree search-based self-organizing multi-agent system (MCTS-MAS) solution

Phase transition phenomenon: A compound measure analysis

Self-Organizing Multi-Agent Systems (SO-MAS) are defined as a set of autonomous entities called agents interacting together in order to achieve a given task. Generally, the development process of these systems is based on the bottom-up approach which focuses on the design of the entities individual behavior. The main question arising when developing SO-MAS is how to insure that the designed entities, when interacting together, will give rise to the desired behavior? Our proposition to deal with this question is to use formal methods. We propose a correct by construction method for systematic design of SO-MAS based on the use of design patterns and formal stepwise refinements. Our work gives guidelines to assist the designer when developing the individual behavior of the entities and prove its correctness at the early stages of the design process. The method is illustrated with the foraging ants’ case study.

Smart cities are the expected result of the intensive use of Information and Communication Technologies (ICT) in our daily life. They are the culmination of the great progress that has been made in ICT in the last few years. Smart cities aim to efficiently, sustainably, securely, and reliably manage critical infrastructures such as power systems, transportation, water systems, etc., for the sake of mankind prosperity, comfort and security. However, the critical infrastructures of future smart cities are expected to be large complex critical infrastructures (LCCIs) that need to be autonomous or self-adaptive to be able to survive in critical unpredictable situations. This chapter presents a new approach based on self-organizing multi-agent systems (So-MAS) for modeling and engineering future self-adaptive LCCIs. So-MAS are MAS that have the capability to dynamically and autonomously reorganize themselves to adapt the dynamic changes of work environment. Further, the proposed approach adopts a novel MAS organizational model (called as NOSHAPE) provided in [1, 2] designed to enable large-scale MAS to adaptively self-organize. Based on a simulation environment, a performance evaluation has been conducted that shows how the proposed approach is able to deal with the dynamic unanticipated work environment behaviors. Up to 47% of performance improvement has been achieved with the proposed approach compared to conventional organizational techniques in MAS (i.e. federation). Further future research is still required to address important issues of future smart cities and their associated LCCIs such as security, and resiliency.

A Busy March Meeting Is Brewing in Seattle

Phase transition and critical phenomenon in traffic flow model with velocity-dependent sensitivity

Multiagent Systems (MASs) have multiple different characteristics, such as autonomy, and asynchronous and social features, which make these systems difficult to understand. Thus, there is a lack of procedures guaranteeing that multiagent systems once implemented would behave as desired. Determining the reliability of such systems is further complicated by the fact that current agent-based approaches may also involve non-deterministic characteristics, such as learning, self-adaptation and self-organization (SASO). Nonetheless, there is a gap in the literature regarding the testing of systems with these features. This paper presents an approach based on metadata and the publish-subscribe paradigm to develop test applications that address the process of failure diagnosis in a self-organizing MAS. The novelty of the proposed approach involves its ability to test self-organizing MAS systems in the context of local and global behavior. To illustrate the use of this approach, we developed a self-organizing MAS system based on the Internet of Things (IoT), which simulates a set of smart street lights, and we performed functional ad-hoc tests. The street lights need to interact with each other in order to achieve the global goals of reducing energy consumption and maintaining the maximum value of visual comfort in illuminated areas. To achieve these global behaviors, the street lights develop local behaviors automatically through a self-organizing process based on machine-learning algorithms.

Thermodynamics of phase transition in Reissner–Nordström–de Sitter spacetime

The hard computational problems, such as the traveling salesman problem (TSP), are relevant to many tasks of practical interest, which normally can be well formalized but are difficult to solve. This paper presents an extended multiagent optimization system, called MAOSE, for supporting cooperative problem solving on a virtual landscape and achieving high-quality solution(s) by the self-organization of autonomous entities. The realization of an optimization algorithm then can be described in three parts: a) encode the representation of the problem, which provides the virtual landscape and possible auxiliary knowledge; b) construct the memory elements at the initialization stage; and c) design the generate-and-test behavior guided by the law of socially-biased individual learning, through tailoring to the domain structure. The implementation is demonstrated on the TSP in details. The extensive experimental results on real-world instances in TSPLIB show its efficiency as comparing to other algorithms.

VO2, which exhibits semiconductor-metal phase transition characteristics occurring on a picosecond time scale, holds great promise for ultrafast terahertz modulation in next-generation communication. However, as of now, there is no reported prototype for an ultrafast device. The temperature effect has been proposed as one of the major obstacles. Consequently, reducing the excitation threshold for the phase transition would be highly significant. The traditional strategy typically involves chemical doping, but this approach often leads to a decrease in phase transition amplitude and a slower transition speed. In this work, we proposed a design featuring a highly conductive MXene interfacial layer between the VO2 film and the substrate. We demonstrate a significant reduction in the phase transition threshold for both temperature and laser-induced phase transition by adjusting the conductivity of the MXene layers with varying thicknesses. Our observations show that the phase transition temperature can be decreased by 9 °C, while the pump fluence for laser excitation can be reduced by as high as 36%. The ultrafast phase transition process on a picosecond scale, as revealed by the optical-pump terahertz-probe method, suggests that the MXene layers have minimal impact on the phase transition speed. Moreover, the reduced phase transition threshold can remarkably alleviate the photothermal effect and inhibit temperature rise and diffusion in VO2 triggered by laser. This study offers a blueprint for designing VO2/MXene hybrid films with reduced phase transition thresholds. It holds significant potential for the development of low-power, intelligent optical and electrical devices including, but not limited to, terahertz modulators based on phase transition phenomena.

Phase transition and critical phenomena in magnetic multilayer systems are studied in terms of Ginzburg–Landau mean-field theory. Detailed calculations are carried out for a system consisting of a layer of finite thickness coupled to a semi-infinite bulk magnet. Correlation functions are derived and the shift in critical point with the overlayer thickness and coupling between the neighboring layer is evaluated. A new critical exponent ν̃=1 is derived for the divergence of the effective extrapolation length at the interface with temperature and/or layer thickness.

Percolation on interdependent networks with cliques and weak interdependence

We study thermodynamics and critical behaviors of higher-dimensional Lovelock black holes with non-maximally symmetric horizons in the canonical ensemble of extended phase space. The effects from non-constancy of the horizon of the black hole via appearing two chargelike parameters in thermodynamic quantities of third-order Lovelock black holes are investigated. We find that Ricci flat black holes with nonconstant curvature horizon show critical behavior. This is an interesting feature that is not seen for any kind of black hole in Einstein or Lovelock gravity in the literature. We examine how various interesting thermodynamic phenomena such as standard first-order small-large black hole phase transition, a reentrant phase transition, or zeroth order phase transition happens for Ricci flat, spherical, or hyperbolic black holes with nonconstant curvature horizon depending on the values of Lovelock coefficient and chargelike parameters. While for a spherical black hole of third order Lovelock gravity with constant curvature horizon phase transition is observed only for $7\leq d \leq11$, for our solution criticality and phase transition exist in every dimension. With a proper choice of the free parameters, a large-small-large black hole phase transition occurs. This process is accompanied by a finite jump of the Gibbs free energy referred to as a zeroth-order phase transition. For the case $\kappa=-1$ a novel behavior is found for which three critical points could exist.