Implementasi Agent-Based Modeling and Simulation dalam Evakuasi Keadaan Darurat

Teknik penyelamatan diri setiap orang dalam keadaan darurat seperti kebakaran di dalam sebuah gedung seringkali justru menjadi berbahaya ketika hal tersebut merugikan orang lain, seperti saling berdesakan yang dapat membahayakan nyawa diri sendiri maupun orang lain. Simulasi evakuasi sekarang menjadi perhatian khusus pada ilmuwan untuk mengurangi resiko kecelakaan yang dapat merugikan korban. Simulasi menggunakan metode agent-based dilakukan untuk mengetahui efek dari setiap atribut yang dimiliki oleh setiap orang. Hasilnya merupakan representasi dari keadaan nyata yang disimulasikan sesuai dengan perilaku manusia. Pada akhirnya, simulasi ini menghasilkan suatu kondisi di mana mirip dengan kondisi aslinya

Agent Based Modeling and Simulation: An Informatics Perspective

The term computer simulation is related to the usage of a computational model in order to improve the understanding of a system's behavior and/or to evaluate strategies for its operation, in explanatory or predictive schemes. There are cases in which practical or ethical reasons make it impossible to realize direct observations: in these cases, the possibility of realizing 'in-machina' experiments may represent the only way to study, analyze and evaluate models of those realities. Different situations and systems are characterized by the presence of autonomous entities whose local behaviors (actions and interactions) determine the evolution of the overall system; agent-based models are particularly suited to support the definition of models of such systems, but also to support the design and implementation of simulators. Agent-Based models and Multi-Agent Systems (MAS) have been adopted to simulate very different kinds of complex systems, from the simulation of socio-economic systems to the elaboration of scenarios for logistics optimization, from biological systems to urban planning. This paper discusses the specific aspects of this approach to modeling and simulation from the perspective of Informatics, describing the typical elements of an agent-based simulation model and the relevant research.Multi-Agent Systems, Agent-Based Modeling and Simulation

Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives

Agent-based modeling and simulation has evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. Integrating large language models into agent-based modeling and simulation presents a promising avenue for enhancing simulation capabilities. This paper surveys the landscape of utilizing large language models in agent-based modeling and simulation, examining their challenges and promising future directions. In this survey, since this is an interdisciplinary field, we first introduce the background of agent-based modeling and simulation and large language model-empowered agents. We then discuss the motivation for applying large language models to agent-based simulation and systematically analyze the challenges in environment perception, human alignment, action generation, and evaluation. Most importantly, we provide a comprehensive overview of the recent works of large language model-empowered agent-based modeling and simulation in multiple scenarios, which can be divided into four domains: cyber, physical, social, and hybrid, covering simulation of both real-world and virtual environments. Finally, since this area is new and quickly evolving, we discuss the open problems and promising future directions.Comment: 37 page

An Agent-Based Model of Behavior in “Beauty Contest” Games

Recently, computer simulation, particularly agent-based modeling, has grown in popularity as a method to uncover macro patterns and developments that emerge from simple micro behavior. The present paper combines both techniques by using protocol analysis to uncover player strategies in an experiment and encoding those strategies in an agent-based computer simulation. In particular, Keynes’ (1936) beauty contest analogy is simulated in a number-guessing context. Several researchers have conducted experiments asking subjects to play “p-beauty contest games” in order to compare the experimental results with those predicted by the game-theoretic, deductive reasoning concept of iterated dominance. Our results are compared with those found experimentally in order to demonstrate the usefulness of a combining agent-based modeling with protocol analysis.Agent-Based modeling; Beauty contest games

Agent-based simulation of the learning dissemination on a Project-Based Learning context considering the human aspects

This work presents an agent-based simulation (ABS) of the active learning process in an Electrical Engineering course. In order to generate input data to the simulation, an active learning methodology developed especially for part-time degree courses, called Project-Based Learning Agile (PBLA), has been proposed and implemented at the Regional University of Blumenau (FURB), Brazil. Through the analysis of survey responses obtained over five consecutive semesters, using partial least squares path modeling (PLS-PM), it was possible to generate data parameters to use as an input in a hybrid kind of agent-based simulation known as PLS agent. The simulation of the scenario suggests that the learning occur faster when the student has higher levels of humanist's aspects as self-esteem, self-realization and cooperation.Comment: 8 pages, 6 figures, minor correction

CFBM - A Framework for Data Driven Approach in Agent-Based Modeling and Simulation

Recently, there has been a shift from modeling driven approach to data driven approach in Agent Based Modeling and Simulation (ABMS). This trend towards the use of data-driven approaches in simulation aims at using more and more data available from the observation systems into simulation models [1, 2]. In a data driven approach, the empirical data collected from the target system are used not only for the design of the simulation models but also in initialization, evaluation of the output of the simulation platform. That raises the question how to manage empirical data, simulation data and compare those data in such agent-based simulation platform. In this paper, we first introduce a logical framework for data driven approach in agent-based modeling and simulation. The introduced framework is based on the combination of Business Intelligence solution and a multi-agent based platform called CFBM (Combination Framework of Business intelligence and Multi-agent based platform). Secondly, we demonstrate the application of CFBM for data driven approach via the development of a Brown Plant Hopper Surveillance Models (BSMs), where CFBM is used not only to manage and integrate the whole empirical data collected from the target system and the data produced by the simulation model, but also to initialize and validate the models. The successful development of the CFBM consists not only in remedying the limitation of agent-based modeling and simulation with regard to data management but also in dealing with the development of complex simulation systems with large amount of input and output data supporting a data driven approach