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Recent advancements in large language models (LLMs) have led to the creation of intelligent agents capable of performing complex tasks. This paper introduces a novel LLM-based multimodal agent framework designed to operate smartphone…
Multiagent reinforcement learning, as a prominent intelligent paradigm, enables collaborative decision-making within complex systems. However, existing approaches often rely on explicit action exchange between agents to evaluate action…
The domain of numerical simulation is a place where the parallelization of numerical code is common. The definition of a numerical context means the configuration of resources such as memory, processor load and communication graph, with an…
Understanding mobility, movement, and interaction in archaeological landscapes is essential for interpreting past human behavior, transport strategies, and spatial organization, yet such processes are difficult to reconstruct from static…
The advancement of mobile GUI agents has opened new opportunities for automating tasks on mobile devices. Training these agents requires large-scale high-quality data, which is prohibitively expensive when relying on human labor. Given the…
The rapidly growing field of network analytics requires data sets for use in evaluation. Real world data often lack truth and simulated data lack narrative fidelity or statistical generality. This paper presents a novel, mixed-membership,…
We propose a method for analyzing the distributed random coordinate descent algorithm for solving separable resource allocation problems in the context of an open multiagent system, where agents can be replaced during the process. In…
E-learning is nowadays one of the most interesting of the "e- " domains available through the Internet. The main problem to create a Web-based, virtual environment is to model the traditional domain and to implement the model using the most…
This paper addresses the limitations of a single agent in task decomposition and collaboration during complex task execution, and proposes a multi-agent architecture for modular task decomposition and dynamic collaboration based on large…
Agent-based modeling approaches represent the state-of-art in modeling travel demand and transportation system dynamics and are valuable tools for transportation planning. However, established agent-based approaches in transportation rely…
Agent-based simulation is an indispensable paradigm for studying complex systems. These systems can comprise billions of agents, requiring the computing resources of multiple servers to simulate. Unfortunately, the state-of-the-art…
In Wireless sensor networks data aggregation with hundreds and thousands of sensor nodes is very complex task. Recently, mobile agents have been proposed for efficient data dissemination in sensor networks. In the traditional client/server…
Traditional AI reasoning techniques have been used successfully in many domains, including logistics, scheduling and game playing. This paper is part of a project aimed at investigating how such techniques can be extended to coordinate…
A mobile computing system is a distributed system in which at least one of the processes is mobile. They are constrained by lack of stable storage, low network bandwidth, mobility, frequent disconnection and limited battery life.…
Large-language models (LLMs) have demonstrated powerful problem-solving capabilities, in particular when organized in multi-agent systems. However, the advent of such systems also raises several questions on the ability of a complex network…
In this paper we focus on Internet-based simulation, a form of distributed simulation in which a set of execution units that are physically located around the globe work together to run a simulation model. This setup is very challenging…
This paper deals with solving distributed optimization problems with equality constraints by a class of uncertain nonlinear heterogeneous dynamic multi-agent systems. It is assumed that each agent with an uncertain dynamic model has limited…
Conventionally, network migration models study competition between emerging and incumbent technologies by considering the resulting increase in revenue and associated cost of migration. We propose to advance the science in the existing…
Agent-Based Models are very useful for simulation of physical or social processes, such as the spreading of a pandemic in a city. Such models proceed by specifying the behavior of individuals (agents) and their interactions, and…
Agent technology, a new paradigm in software engineering, has received attention from research and industry since 1990s. However, it is still not used widely to date because it requires expertise on both programming and agent technology;…