Agent Coordination Research Articles

Intermittent Information-Driven Multi-Agent Area-Restricted Search.

The problem is a two-dimensional area-restricted search for a target using a coordinated team of autonomous mobile sensing platforms (agents). Sensing is characterised by a range-dependent probability of detection, with a non-zero probability of false alarms. The context is underwater surveillance using a swarm of amphibious drones equipped with active sonars. The paper develops an intermittent information-driven search strategy, which alternates between two phases: the fast and non-receptive displacement phase (called the ballistic phase) with a slow displacement and sensing phase (called the diffusive phase). The proposed multi-agent search strategy is carried out in a decentralised manner, which means that all computations (estimation and motion control) are done locally. Coordination of agents is achieved by exchanging the data with the neighbours only, in a manner which does not require global knowledge of the communication network topology.

Distributed agent-based building grey-box model identification

The paper deals with an identification (calibration) of a building thermal model as a crucial part of modern control algorithms. It describes a modelling issue and parameter identification approach. There is presented an identification approach using a so called dual decomposition method which decomposes a large optimization problem into smaller local ones which are then solved by local agents. The local models are found using a grey-box calibration and by a coordination of agents’ mutual shared parameters a global consistency is obtained.The proposed method is tested on two examples; one is basically trivial, in the latter one, more complex, a model of a building simulated in the EnergyPlus program is obtained and offers promising results for (predictive) control-oriented purposes.

ANALYTICAL REVIEW OF MULTI-AGENT REINFORCEMENT LEARNING PROBLEMS

This paper is devoted to the problem of collective artificial intelligence in solving problems by intelligent agents in external environments. The environments may be: fully or partially observable, deterministic or stochastic, static or dynamic, discrete or continuous. The paper identifies problems of collective interaction of intelligent agents when they solve a class of tasks, which need to coordinate actions of agent group, e. g. task of exploring the territory of a complex infrastructure facility. It is revealed that the problem of reinforcement training in multi-agent systems is poorly presented in the press, especially in Russian-language publications. The article analyzes reinforcement learning, describes hierarchical reinforcement learning, presents basic methods to implement reinforcement learning. The concept of macro-action by agents integrated in groups is introduced. The main problems of intelligent agents collective interaction for problem solving (i. e. calculation of individual rewards for each agent; agent coordination issues; application of macro actions by agents integrated into groups; exchange of experience generated by various agents as part of solving a collective problem) are identified. The model of multi-agent reinforcement learning is described in details. The article describes problems of this approach building on existing solutions. Basic problems of multi-agent reinforcement learning are formulated in conclusion.

Smart Binders for Silicon Based Composite Electrode in Li-Ion Batteries

Silicon is one of the most promising alloying anode materials for Li-ion batteries thanks to its high specific and volumetric capacity. In comparison with the commercially available graphite, silicon delivers 10 times higher specific capacity (up to 3600 mA.h.g-1) and 3 times higher volumetric capacity ( up to 2200 mA.h.cm-3) [1]. However, silicon suffers from high volumic expansion upon lithiation (up to 280 %). It induces the pulverization of the micrometric silicon particle, the perpetual solid electrolyte interface renewal and decohesion between constitutive elements of the electrode, drastically reducing its lifespan [2].To tackle those issues we propose the formulation of composite electrode with improved binder. It is composed of carboxymethyl cellulose sodium salt (NaCMC, as a binding network) and zinc sulfate dissolved in a pH 3 buffer solution (composed of citric acid and potassium hydroxide). The originality and improvement comes from the use Zn2+ ions as coordination agents, binding to carboxylate groups from the CMC and citric acid. Among benefits, we believe that the coordination helps to mitigate the stress inside the electrode because of the improved reticulation of the network, thus improving its resilience [3]. To support this hypothesis, we provide physico-chemical characterizations of the binder as well as the electrochemical performances of our electrodes. [1] M.N. Obrovac, V.L. Chevrier, Alloy Negative Electrodes for Li-Ion Batteries. Chem. Rev. 2014, 114, 11444-11502. [2] A. Etiemble, A. Tranchot, T. Douillard, H. Idrissi, E. Maire, L. Roué., Evolution of the 3D Microstructure of a Si-Based Electrode for Li-Ion Batteries Investigated by FIB/SEM Tomography, J. Electrochem. Soc. 2016,163, A1550-A1559 [3] D. Mazouzi, R. Grissa, M. Paris, Z. Karkar, L. Huet, D. Guyomard, L. Roué, T. Devic, B. Lestriez, CMC-citric acid Cu(II) cross-linked binder approach to improve the electrochemical performance of Si-based electrodes. Electrochim. Acta 2019, 304, 495-504.

A language and framework for dynamic component ensembles in smart systems

Smart system applications (SSAs)—a heterogeneous landscape of applications of Internet of things, cyber-physical systems, and smart sensing systems—are composed of autonomous yet inherently cooperating components. An important problem in this area is how to hoist the cooperation of software components forming dynamic groups—ensembles—at the architectural level of an SSA. This is hard since ensembles can overlap, be nested, and be dynamically formed and dismantled based on several criteria. A related problem is how to combine component and ensemble specification with a well-established language supported on multiple platforms. To target these problems, we propose a specification and implementation language Trait-based COmponent Ensemble Language (TCOEL) based on Scala internal DSL, to describe both the architecture and formation of dynamic ensembles of components and their functional internals. To raise the level of expressivity, we introduce the concept of domain-specific extensions (traits) to the TCOEL core to reflect different paradigms’ concerns—such as movement in a 2D map, state-space modeling of physical processes, and statistical reasoning about uncertainty. This allows for configuring TCOEL for the needs of a specific SSA use case and, at the same time, facilitates reuse. To evaluate TCOEL, we show how it can be beneficially used in addressing the coordination of agents in a RoboCup Rescue Simulation application.

Crystalline chromium electroplating with high current efficiency using chloride hydrate melt-based trivalent chromium baths

Chromium (Cr) plating using trivalent chromium has been investigated as a replacement for the highly-toxic hexavalent chromium bath. Herein, we report novel chromium plating baths using hydrate-melts. Hydrate-melts have been investigated in recent years as an electrolyte for aqueous Li-ion batteries with a wide electrochemical window, and can be used as an electroplating bath in which the reduction of protons, i.e., bath decomposition, is suppressed. By using a hydrate-melt for electroplating with trivalent chromium, the increase of local pH during electrolysis is suppressed and generation of the electrochemically-inert oligomer of chromium hydroxide can be avoided. Crystalline chromium electrodeposits were successfully obtained from the hydrate-melt-based aqueous baths, which had not been possible with the conventional trivalent chromium process requiring organic coordination agents. Moreover, a current efficiency greater than 80% was achieved. The hydrate-melt-based aqueous bath, with low material cost, is a promising candidate for industrial trivalent chromium plating.

Post-disruption performance recovery to enhance resilience of interconnected network systems

ABSTRACT Mitigating the effect of disruptive events at the operating phase of complex systems therefore improving the systems’ resilience is an important yet challenging task. To improve the resilience, one way is to enhance the failure restoration capability with appropriate performance recovery strategies. However, considering different characteristics of disruptive events, the challenge is to develop a generally applicable framework to optimally coordinate different recovery strategies within a given budget. In order to tackle the challenge, this paper presents a post-disruption recovery framework for networked systems to optimize the performance. In this study, coordination of different recovery agents is achieved by using mathematical programming technique, while the assignment of the required resource for restoration is found by a heuristic algorithm. Case studies based on IEEE test feeders are used to demonstrate the feasibility of the developed framework, as well as the effects of optimal resource allocation nested in the restoration framework.

Effects of a Macromolecule Spirocyclic Inflatable Flame Retardant on the Thermal and Flame Retardant Properties of Epoxy Resin.

A new strategy for the preparation of an integrated three-source intumescent flame retardant (IFR) has been developed to improve the flame-retardant and smoke suppression performance of epoxy resin (EP) with a synergistic flame retardant effect. Herein, the synthesis of a macromolecular spirocyclic phosphorus/nitrogen-containing IFR poly sulfonamide spirocyclic pentaerythritol bisphosphonate (SAPC) is reported via a two-step method that uses pentaerythritol, phosphorus oxychloride and sulfonamide (SAA) as raw materials. Subsequently, the SAPC was incorporated into EP to prepare the composite to investigate its thermal stability, flame retardancy, and smoke suppression performance. Herein, a differential scanning calorimetry (DSC) analysis showed that the addition of SAPC increased the glass transition temperature (Tg) of the composite. Cone test results indicated that the incorporation of 8 wt % SAPC significantly improved the flame-retardant performance for the composite, with a 43.45% decrease in peak of heat release rate, a 28.55% reduction in total heat release, and a 30.04% decrease in total smoke release. Additionally, the composite received the V-0 rating in a UL-94 vertical burning test, accompanied by the “blowout” phenomenon. After the addition of SAPC, the amount of flammable gas products from the EP composite decomposition was obviously suppressed, and the amount of non-flammable as was increased. All of this suggests a good dilution role of SAPC. There are enough reasons to believe that the enhanced flame-retardant and toxicity suppression performance for the EP composite can be attributed to the good coordination of carbonization agent, acid source, and blowing agent in the SAPC structure.

Coordinating the Behavior of Different Agents in Distribution Networks – A Review

This paper provides a detailed overview of the current state of scientific literature on the coordination of different agents in smart distribution systems. The coordination of agents can be market-driven or network-related. As an important market-driven measure, approaches that allow to reflect time-variable retail tariffs are investigated. Trading flexibility at smart markets is considered to be a central approach for network-related coordination in the future. As market-driven and network-related coordination of agents can be contradictory, also literature that considers both is discussed. Finally, a conceptual framework for the analysis of alternative market regimes in distribution networks is developed on basis of the reviewed literature.

Towards a new supporting platform for collaboration in industrial diagnosis within an agent-based WEB DSS

The main objective of this study is to provide a professional social network which is integrated within an agent-based WEB DSS. This DSS network will facilitate interaction, discussion, and the sharing of information among production operators, especially to deal with nominal situations of resource faults. The coordination among the agents in our approach is made possible by a dynamic agent coordination protocol. The general architecture is based on agents named: production agent (PA), ontology agent (OA), evaluator agent (EA), and coordinator agent (COA). The coordination protocol that is applied comprised a set of behaviours used to maintain and control the messages exchanges among the agents. Learning features enable these agents to gain more time in calculation and executions. As a representation of the agent's common knowledge, domain ontology has been developed to represent major generic concepts in the industrial domain. Analytical hierarchy process (AHP) methodology is applied to evaluate sorting solutions in respect of human participants' preferences. In this study, we choose as a field of application: ALFATRON electronics industry.

Stochastic Valuation of Revenue-Collecting Tokens in Cryptoeconomic Organizations

Cryptoeconomic systems are an emerging type of complex systems that are viewed as a way to steer economic systems and organizations through agents coordination and incentives. However, very little is known about the inherent economic flows of such systems. In this paper, in order to provide intuition on the incentive structures, we draw a first sketch of financial streams in cryptoeconomic organizations. We then present a formal stochastic model of revenue-collecting tokens valuation. With the aim to account for the stochastic nature of this revenue, the financial input of such an organization is assumed to follow a geometric Brownian motion.

Optimized Control for Human-Multi-Robot Collaboration via Multi-Agent Adaptive Dynamic Programming

Abstract In this paper we consider the problem of controlling the dynamic behavior of the robot agents while collaborating with the human worker. The presented dynamic behavior control method leads to achieving optimized interaction performance of the human-multi-robot collaboration system. We investigate in depth the dynamics equation of the robot agents collaborating with the human worker. Considering the unknown parameters in the system dynamics, the adaptive dynamic programming method is utilized to deal with the optimized interaction control problems during human-multi-robot collaboration process. To achieve the coordination of the multi robot agents, multi-agent adaptive dynamic programming method is employed in this paper. The neural networks with one hidden layer are utilized to approximate both the unknown system dynamics as well as the optimized cost function. The simulation studies verify the effectiveness of the presented algorithm.

ИНТЕГРАЛЬНОЕ ОБЩЕСТВО, ИНТЕГРАЛЬНАЯ ЭКОНОМИКА, ИНТЕГРАЛЬНЫЙ УЧЕНЫЙ (ПАМЯТИ Г.Н. ЦАГОЛОВА)

In the article, the concepts of integral society and integral economy are considered in the context of the general methodology of integralism, developed by Pitirim Sorokin and improved by G.N. Tsagolov. Analysis of the natural location's peculiarities and the historical trajectory of countries' socio-economic development allows them to be divided into four groups: object, project, process, and environmental. This approach reveals the predisposition of countries to market / planned methods of coordination of in-country agents. The article shows that the most relevant for Russia is the so-called mixed economy in which capitalism elements are organically intertwined with elements of socialism. Studying the works of G.N. Tsagolov makes it possible to shed light on specific forms of interaction between elements of the capitalist and socialist modes in Russia's mixed economy.

Intention Mining Data preprocessing based on Multi-Agents System

Abstract Today vast and diverse event records of applications exist for almost every scientific domain, making their integration and intelligent exploitation challenging. Indeed, complex data require expressive data representation models. This work deals with the intention mining that is a very active and promising research area. Performance, flexibility, and adaptation are the biggest challenges for intention mining. Those issues have been illustrated from research on method engineering and guidance. Intention mining is the ability to predict a user’s goals. Knowing the user’s intention can support the decision-making of the network administrators. In addition, the user-friendliness is another big challenge to the intention mining in this paper. For this, based on the communication and coordination of intelligent Agents, a new multi-Agents based System approach is gathered in order to discover an intentional process model and provide specific recommendations. In addition, the input of intention mining is the trace of activities, which is an unstructured file because the activities are distributed from different sources. However, the dataset that will be used in intention mining must be well structured and filtered, so often some efforts are required to filter the relevant data. The main input of all algorithm used to discover intentional process model is the log file (traces activities), which is unstructured dataset and not ready to be feed as-is to machine learning algorithm. Therefore, this paper aims to describe the data preprocessing steps, which transform the unstructured log file to a structured one.

OMCM-CAS: organisational model and coordination mechanism for self-adaptation and self-organisation in collective adaptive systems

Collective adaptive system (CAS) is a distributed system which has heterogeneous agents with different capabilities in large scale. Having self-adaptiveness in CAS can address problems about coordination and cooperation of agents. This research compares self-organisation (as a solution for reacting to the changes in distributed systems) with self-adaptation in a broader view and identifies the differences and correlations. Also, it considers the applicability of coordination, reflection and architectural approaches in both domains and presents a hybrid approach. Organisational models for self-organisation in distributed environment have studied and have got analysed. A new combined organisational model has been introduced based on the benefits and weak points of current organisational models. Based on presented organisational model, a coordination mechanism has been introduced for facilitating the cooperation in CAS. A Case study have been discussed and simulated and simulation results support the applicability and effectiveness of the presented organisational model and coordination mechanism.

Analysis of Solvent Effect on Formation Constants and Speciation of Cobalt(II), Copper(II) and Lead(II) Complexes of L-Methionine and Uracil

The analysis of coordination of chelating agents to metal ions in the formation of complexes under different experimental conditions provide information on the effects of the conditions on the extent of the coordination of the ligands to the metal ions for potential applications in bioinorganic and environmental Inorganic Chemistry. The effect of solvent on the coordination of L-methionine (primary ligand) and uracil (secondary ligand) to Co(II), Cu(II) and Pb(II) ions in the formation of binary and ternary complexes have been potentiometrically investigated in water and 40% (v/v) ethanol- water media at 27 °C and ionic strength of 0.02 mol dm–3was maintained by using NaNO3. The proton-ligand stability constants and formation constants of the binary and ternary systems were established under the experimental conditions. The formation constants of the ternary complexes were numerically compared with the corresponding binary complexes in terms of Δ log K and percentage relative stabilization (%RS). Speciation of the metal ions, binary and ternary complexes as a function of pH in the solutions was investigated by using HYSS program. The ligands were observed to form more stable ternary complexes than binary complexes. The proton-ligand stability constants the ligands and the formation constants of the metal complexes were found to be higher in 40% (v/v) ethanol-water than water. The distribution of the species revealed a decrease in the metal ion concentrations with increase in the concentrations of the binary and ternary as pH increased. The chelating agents interacted strongly with the metal ions and showed different selectivity towards the metals ions. These properties can be exploited in combating metal poisoning, separating the metals and expounding the bioinorganic chemistry of the metal ions and the ligands.

Simulation Research on the Effectiveness of a Multiagent Mine Safety Supervision System and Its Verification

A Computable Mine Safety Supervision (CMSS) model is constructed based on agent-based modeling and simulation (ABMS) technology and the conservation of resources (COR). This model aims to solve the mining safety problems involved with illegal mining operations and burnout among mining supervisors, in China. The model includes several types of agents: supervision agents, decision support agents, functional coordination agents, and miner agents, and it uses the Netlogo simulation platform to simulate the influence of reward and punishment on agent behavior. The simulation determines the decision support degree to gauge the influence of functional coordination and miner behavior on the burnout rate of supervision agents. We analyze the macroscopic emergence law of the simulation results. The results show the following: (1) Job Situation Adaptability (JSA) ∈ [−6.02, 2.64] ∪ [16.9, 21.93], which uses a reward strategy to guide miners to choose safe behavior and (2) JSA ∈ [2.64, 16.9], which uses a punishment strategy to restrict unsafe behavior. The decision support coefficient Sc has the greatest influence on the supervision agent’s job burnout. The functional coordination coefficient Fc has the second highest influence on job burnout and the processing effectiveness coefficient Ec has the least influence. According to the simulation results, suggestions for improving the mine safety supervision system are put forward and an improved safety management decision-making basis for reducing mine accidents is provided.

Integrated yet distributed operations planning approach: A next generation manufacturing planning system

Present paper envisages the need for an innovative operations planning system to handle the challenges and opportunities offered by next industrial revolution called Industry 4.0 or smart manufacturing. In specific, to embrace the increasing level of automation in manufacturing industries, the obligation of joint consideration of multiple operations functions is realized. On the other hand, quick response to dynamic conditions created by machine failures, change in demand, uncertainty in supply, etc., is important in captivating the advantages of the digitization in industries. Easing out the computational complexity, imposed by the integration of multiple functions, therefore, becomes an important aspect of next generation manufacturing planning systems. Consequently, in this paper, an agent-based approach is engineered around the opportunities offered by modern digital factory viz., intelligence at the shop-floor and ubiquity of wireless communications. While intelligence at shop-floor allows distributing the decision-making tasks to various functional agents, the communication among the agents makes it feasible to incite integrated view through the coordination agent. The approach is demonstrated for a representative industrial environment of an automotive plant. Further, comparison over conventional approaches, computational comparison, effect of degree of integration, and performance of the approach under dynamic conditions are investigated. Finally, the approach is comprehensively evaluated to analyze its robustness and implications in various manufacturing settings. This extensive investigation shows that the proposed operations planning system has capability to apprehend the benefits from next generation intelligent factory.

An adaptive distributed Intrusion detection system architecture using multi agents

Intrusion detection systems are used for monitoring the network data, analyze them and find the intrusions if any. The major issues with these systems are the time taken for analysis, transfer of bulk data from one part of the network to another, high false positives and adaptability to the future threats. These issues are addressed here by devising a framework for intrusion detection. Here, various types of co-operating agents are distributed in the network for monitoring, analyzing, detecting and reporting. Analysis and detection agents are the mobile agents which are the primary detection modules for detecting intrusions. Their mobility eliminates the transfer of bulk data for processing. An algorithm named territory is proposed to avoid interference of one analysis agent with another one. A communication layout of the analysis and detection module with other modules is depicted. The inter-agent communication reduces the false positives significantly. It also facilitates the identification of distributed types of attacks. The co-ordinator agents log various events and summarize the activities in its network. It also communicates with co-ordinator agents of other networks. The system is highly scalable by increasing the number of various agents if needed. Centralized processing is avoided here to evade single point of failure. We created a prototype and the experiments done gave very promising results showing the effectiveness of the system.

From Pattern Recognition to Economic Disequilibrium

This article is focused on the economic works of the Soviet machinelearning pioneer Emmanuil Braverman, who published, during the 1970s, a series of papers introducing disequilibrium fixed-price models of the Soviet economy. This highly original theory, developed independently from the Western analyses of disequilibria, proposed rationing mechanisms capable, under some conditions, of bringing a system to the state of equilibrium. However, in a fixed-price economy, equilibria are not necessarily optimal or effective; therefore specific observational and analytic procedures aiming at bringing a system to a better state had to be invented. Braverman interpreted this analytic framework as a “qualitative system of control” of the Soviet economy representing a sort of a third-way solution between neoclassical models of spontaneous coordination of autonomous agents and theories of optimal planning. This innovative approach, very different from the styles of reasoning in mathematical economics of his time, was grounded in his work on pattern recognition and informed by a cybernetic vision of control as information processing and communication in complex systems.