The article considers the problem of finding the optimal on average control of the trajectories of continuous stochastic systems with incomplete feedback. This class of problems includes control problems in which the initial states are described by a...
Distributed constraint satisfaction problems (DisCSPs) are among the widely endeavored problems using agent-based simulation. Fernandez et al. formulated sensor and mobile tracking problem as a DisCSP, known as SensorDCSP In this paper, we adopt a cu...
In today’s dynamic and complex social environments, collaborative human groups play a critical role in addressing a wide range of real-world challenges. Collective problem-solving, the process of finding solutions through the collaboration of i...
The paper addresses the problem of distinguishing the leading agents in the group. The problem is considered in the framework of classification problems, where the agents in the group select the items with respect to certain properties. The suggested...
The Bicycle-sharing System (BSS) has been globally adopted as a sustainable transportation system that helps improve air pollution, public health and traffic congestion. The increased usage of BSSs requires an increased number of rebalancing trucks t...
Unmanned aerial vehicles (UAVs), commonly known as drones, offer unprecedented flexibility for complex missions such as area surveillance, search and rescue, and cooperative inspection. This paper presents a unified evaluation framework for the compa...
This paper presents a new methodology to derive and analyze strategies for a fully decarbonized urban transport system which combines conceptual vehicle design, a large-scale agent-based transport simulation, operational cost analysis, and life cycle...
Imagine a person visiting an urban event. At each moment in time, the person has to weigh up different possible actions and make consecutive decisions. For instance, a person might be hungry or thirsty and would therefore like to go somewhere to eat...
Collaborative problem solving (ColPS) proficiency was developed as a new assessment for the Programme for International Student Assessment (PISA) in the 2015 international evaluation of student skills and knowledge. The assessment framework defined b...
Water resource allocation is the process of assessing and determining a mechanism on how water should be distributed among different regions, sectors and users. Over the recent decades, the optimal solution for water resource allocation has been expl...
Urban logistics plays a crucial role in ensuring the efficient movement of goods in densely populated areas. This study examines the PDP-TW in an urban logistics context using an integrated approach that combines an agent-based simulation model and a...
This article introduces an innovative hybrid methodology that integrates deterministic Mixed-Integer Linear Programming optimization with stochastic Agent-Based Simulation to address the PDP-TW. The approach is applied to real-world operational data...
The development of e-systems has given consumers and businesses access to a plethora of information, which has complicated the process of decision making. Document classification is one of the main decisions that any business adopts in their decision...
In today’s complex and dynamic transportation networks, increasing energy costs and adverse environmental impacts necessitate the efficient transport of goods or raw materials across a network to minimize all related costs through vehicle assig...
Cross-domain cooperative task allocation is a complex and challenging issue in the field of multi-agent task allocation that requires urgent attention. This paper proposes a task allocation method based on the multi-strategy improved dung beetle opti...
Path exits for transhumant livestock are a major problem in many Sub-Saharan African countries. These problems contribute to many community conflicts. Several solutions are currently being studied, including dialogues between stakeholders. In this pa...
The Discrete Network Design Problem (DNDP) has mainly been used in unimodal infrastructure planning in small cities. This is because it does not consider differences in traveler mode choice. To address the challenges of multimodal transportation infr...
One of the complexities of social systems is the emergence of behavior norms that are costly for individuals. Study of such complexities is of interest in diverse fields ranging from marketing to sustainability. In this study we built a conceptual Ag...
In this paper, the essence and optimization objectives of the hull parts path optimization problem of CNC laser cutting are described, and the shortcomings of the existing optimization methods are pointed out. Based on the optimization problem of the...
In this paper, we describe a comparative analysis of a bus route scheduling problem as part of timetable trips. We consider the current uptake of electric buses as a viable public transportation option that will eventually phase out the diesel-engine...
The problem of multi-agent remote sensing for the purposes of finding survivors or surveying points of interest in GPS-denied and partially observable environments remains a challenge. This paper presents a framework for multi-agent target-finding us...
In the research and development of multiagent systems (MAS), one of the central issues is how to conciliate the autonomy of the agents with a desirable and stable behavior of the MAS as a whole. Agent organizations have been proposed as a suitable me...
Multiagent systems (MASs) allow facing complex, heterogeneous, distributed problems difficult to solve by only one software agent. The world of video games provides problems and suitable environments for the use of MAS. In the field of games, Unity i...
In this work, the problem of exploring an unknown environment with a team of agents and search different targets on it is considered. The key problem to be solved in multiple agents is choosing appropriate target points for the individual agents to s...
In this paper, we address the utility maximization problem of an infinitely lived agent who has the option to increase their income. The agent can increase their income at any time, but doing so incurs a wealth cost proportional to the amount of the...
Multi-access edge computing (MEC) is a novel computing paradigm that leverages nearby MEC servers to augment the computational capabilities of users with limited computational resources. In this paper, we investigate the computational offloading prob...
A pickup and delivery problem by multiple agents has many applications, such as food delivery service and disaster rescue. In this problem, there are cases where fuels must be considered (e.g., the case of using drones as agents). In addition, there...
The popularity of commercial unmanned aerial vehicles has drawn great attention from the e-commerce industry due to their suitability for last-mile delivery. However, the organization of multiple aerial vehicles efficiently for delivery within limita...
Context: At present, sensor-based systems are widely used to solve distributed problems in changing environments where sensors are controlled by intelligent agents. On Multi-Agent Systems, agents perceive their environment through such sensors, actin...
We investigate the integration of several additional efficient techniques that improve a solution method for the lifelong multiagent pickup-and-delivery (MAPD) problem to reduce the redundancy in the concurrent task execution and space usage of a war...
In this paper, we focus on the nonsmooth composite optimization problems over networks, which consist of a smooth term and a nonsmooth term. Both equality constraints and box constraints for the decision variables are also considered. Based on the mu...
When it comes to modelling complex systems using an agent-based approach, there is a problem of choosing the appropriate parameter optimisation technique. This problem is further aggravated by the fact that the parameter space in complex agent-based...
This paper studies the consensus problem for heterogeneous multi-agent systems with output saturations. We consider the agents to have different dynamics and assume that the agents are neutrally stable and that the communication graph is undirected....
In this paper, we focus on developing self-organizing algorithms aimed at solving, in a distributed way, the coverage problem in Wireless Sensor Networks (WSNs). For this purpose, we apply a game-theoretical framework based on an application of a var...
One of the possible approaches to solving difficult optimization problems is applying population-based metaheuristics. Among such metaheuristics, there is a special class where searching for the best solution is based on the collective behavior of de...
Compared with traditional fuel vehicles, battery electric vehicles (BEVs) as a sustainable transportation form can reduce carbon dioxide emissions and save energy, so its market share has great potential. However, there are some problems, such as: Th...
In recent years, unmanned aerial vehicles (UAVs) have been considered an ideal relay platform for enhancing the communication between ground agents, because they fly at high altitudes and are easy to deploy with strong adaptabilities. Their maneuveri...
Recently, multi-agent systems have become widespread as essential technologies for various practical problems. An essential problem in multi-agent systems is collaborative automating picking and delivery operations in warehouses. The warehouse commis...
Autonomous robotic systems operating in the vicinity of other agents, such as humans, manually driven vehicles and other robots, can model the behaviour and estimate intentions of the other agents to enhance efficiency of their operation, while prese...
One of the challenges in multi-agent systems comes from the environmental non-stationarity that policies of all agents are evolving individually over time. Many existing multi-agent reinforcement learning (MARL) methods have been proposed to address...
The aim of the article is to describe a predicate-based logical model for the problem-solving of robots. The proposed article deals with analyses of trends of problem-solving robotic applications for manufacturing, especially for transportations and...
Capture the Flag (CTF) is an important form of competition in cybersecurity, which tests participants’ knowledge and problem-solving abilities. We propose a multi-agent framework based on large language models to simulate human participants and...
Food corruption and spoilage caused by food-borne pathogens and microorganisms is a serious problem. As a result, the demand for antibacterial drugs in food packaging is growing. In this review, biodegradable and non-biodegradable materials for food...
The multi-microgrid (MMG) system has attracted more and more attention due to its low carbon emissions and flexibility. This paper proposes a multi-agent reinforcement learning algorithm for real-time energy management of an MMG. In this problem, the...
An efficient participation of prosumers in power system management depends on the quality of information they can obtain. Prosumers actions can be performed by automated agents that are operating in time-changing environments. Therefore, it is essent...
In non-cooperative multi-agent planning environments, it is essential to have a system that enables the agents’ strategic behavior. It is also important to consider all planning phases, i.e., goal allocation, strategic planning, and plan execution, i...
The optimization of job shop scheduling is pivotal for improving overall production efficiency within a workshop. In demand-driven personalized production modes, achieving a balance between workshop resources and the diverse demands of customers pres...
In this work, the problem of the cooperative visual-based SLAM for the class of multi-UA systems that integrates a lead agent has been addressed. In these kinds of systems, a team of aerial robots flying in formation must follow a dynamic lead agent,...
We present an overview of formation control for multi-agent systems. Multi-agent formation cooperation is important to accomplish assigned tasks more efficiently and safely compared to a single agent. For the way information flows between agents, we...
Artificial intelligence for aircraft guidance is a hot research topic, and deep reinforcement learning is one of the promising methods. However, due to the different movement patterns of destinations in different guidance tasks, it is inefficient to...
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