911 Improvement of Multi-Agent Based Traffic Simulator for Three Dimensional Road Network

Multi-agent formation control is the process in which the teams formed by multiple agents move to specific target or specific direction. The formation method of the linear formation and circular formation are given in this paper, based on the geometric characteristics of the formation formed by multi-agent. The process in which 5 agents arrived at the designated target point and formed a linear formation is achieved through simulation; and 4 agents formed a circular formation and cooperated to carry heavy weights. The result of the three-dimensional simulation shows the feasibility of the method to form multi-agent formations in different environments and different tasks.

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A three-dimensional multi-agent-based model for the evolution of Chagas’ disease

Biosystems ◽

10.1016/j.biosystems.2010.03.007 ◽

2010 ◽

Vol 100 (3) ◽

pp. 225-230 ◽

Cited By ~ 8

Author(s):

Viviane Galvão ◽

José Garcia Vivas Miranda

Keyword(s):

Chagas Disease ◽

Three Dimensional ◽

Agent Based Model ◽

Agent Based ◽

Multi Agent

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MANAGING THE ROAD NETWORK OF URBAN AGGLOMERATION: FORMATION OF THE INFORMATION MODELING

The Russian Automobile and Highway Industry Journal ◽

10.26518/2071-7296-2019-5-606-617 ◽

2019 ◽

Vol 16 (5) ◽

pp. 606-617

Author(s):

T. V. Bobrova ◽

A. A. Andryushenkov

Keyword(s):

Project Management ◽

Road Network ◽

Three Dimensional ◽

Road Transport ◽

Information Modeling ◽

Transport Infrastructure ◽

The Road ◽

Digital Modeling ◽

Multi Agent ◽

The City

Introduction. An analysis of the most well-known agglomeration management models in Russia and abroad has shown that there are no comprehensive solutions in this area yet. The problem of information modeling of control actions on the state and development of the road network of these territorial entities is not well understood and requires further comprehensive research. The purpose of the paper is to formulate the most important principles and methodological approaches for building a modern information system for managing the road infrastructure of urban agglomerations.Methods and models. The designed system based on information modeling technologies of transport interaction processes between corresponding points. The structure of the system presented on the principles of multi-agent project management. The authors identified the types of mathematical models for solving key problems in the framework of design modules by creation of an agglomeration transport framework, ensuring the regulatory requirements of the transport and operational condition of roads and by creation of conditions for the continuous and safe movement of road transport.Results. The architecture of the “Road Network-6D BIM” developed system reflected the relations of two information processes: filling the system with knowledge and forming box solutions using a knowledge bank. The n-D modeling based on three-dimensional projections of structures (3-D) with the addition of digital modeling technologies: calendar terms, resources and financing of objects in the life cycle. The authors tested system elements during the experiment and the implementation of the project for the integrated development of the transport infrastructure of the Omsk agglomeration.Discussion and conclusions. The implementation of the “Road Network-6D BIM” project in the proposed concept makes a definite contribution to solving the problems of managing the road network of the city agglomeration by increasing the level of intellectualization of the tasks at all stages of project management.

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Generating urban structures: A method for urban planning supported by multi-agent systems and cellular automata

10.31219/osf.io/s4crf ◽

2018 ◽

Author(s):

Reinhard Koenig

Keyword(s):

Urban Planning ◽

Cellular Automata ◽

Three Dimensional ◽

Simulation Method ◽

Multi Agent Systems ◽

Agent Based ◽

Generative Process ◽

Urban Structures ◽

Urban Patterns ◽

Multi Agent

This work is based on the concept that the structure of a city can be defined by six basic urban patterns. To enable more complex urban planning as a long-term objective I have developed a simulation method for generating these basic patterns and for combining them to form various structures. The generative process starts with the two-dimensional organisation of streets followed by the parceling of the remaining areas. An agent-based diffusion-contact model is the basis of these first two steps. Then, with the help of cellular automata, the sites for building on are defined and a three-dimensional building structure is derived. I illustrate the proposed method by showing how it can be applied to generate possible structures for an urban area in the city of Munich.

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Multi-Agent Systems in Three-Dimensional Protein Structure Prediction

Advances in Computational Intelligence and Robotics - Multi-Agent-Based Simulations Applied to Biological and Environmental Systems ◽

10.4018/978-1-5225-1756-6.ch011 ◽

2017 ◽

pp. 241-278 ◽

Cited By ~ 1

Author(s):

Leonardo de Lima Corrêa ◽

Márcio Dorn

Keyword(s):

Protein Structure ◽

Protein Structure Prediction ◽

Structure Prediction ◽

Protein Structures ◽

Three Dimensional ◽

Multi Agent Systems ◽

Agent Based ◽

Agent Systems ◽

Tertiary Protein Structure ◽

Multi Agent

Tertiary protein structure prediction in silico is currently a challenging problem in Structural Bioinformatics and can be classified according to the computational complexity theory as an NP-hard problem. Determining the 3-D structure of a protein is both experimentally expensive, and time-consuming. The agent-based paradigm has been shown a useful technique for the applications that have repetitive and time-consuming activities, knowledge share and management, such as integration of different knowledge sources and modeling of complex systems, supporting a great variety of domains. This chapter provides an integrated view and insights about the protein structure prediction area concerned to the usage, application and implementation of multi-agent systems to predict the protein structures or to support and coordinate the existing predictors, as well as it is advantages, issues, needs, and demands. It is noteworthy that there is a great need for works related to multi-agent and agent-based paradigms applied to the problem due to their excellent suitability to the problem.

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Bats Versus Bugs: Collective Behavior of Prey Decreases Predation in a Biologically-Inspired Multi-Agent System

Volume 1: Aerial Vehicles; Aerospace Control; Alternative Energy; Automotive Control Systems; Battery Systems; Beams and Flexible Structures; Biologically-Inspired Control and its Applications; Bio-Medical and Bio-Mechanical Systems; Biomedical Robots and Rehab; Bipeds and Locomotion; Control Design Methods for Adv. Powertrain Systems and Components; Control of Adv. Combustion Engines, Building Energy Systems, Mechanical Systems; Control, Monitoring, and Energy Harvesting of Vibratory Systems ◽

10.1115/dscc2013-3816 ◽

2013 ◽

Author(s):

Yuan Lin ◽

Nicole Abaid

Keyword(s):

Collective Behavior ◽

Dimensional Space ◽

Three Dimensional ◽

Biologically Inspired ◽

Agent Based ◽

Big Brown Bats ◽

Hunting Success ◽

Multi Agent ◽

The Impact ◽

Three Dimensional Space

In this paper, we establish an agent-based model to study the impact of collective behavior of a prey species on the hunting success of predators inspired by insectivorous bats and swarming insects, called “bugs”. In the model, we consider bats preying on bugs in a three-dimensional space with periodic boundaries. The bugs follow one of the two regimes: either they swarm randomly without interacting with peers, or they seek to align their velocity directions, which results in collective behavior. Simultaneously, the bats sense their environment with a sensing space inspired by big brown bats (Eptesicus fuscus) and independently prey on bugs. We define order parameters to measure the alignment and cohesion of the bugs and relate these quantities to the cohesion and the hunting success of the bats. Comparing the results when the bugs swarm randomly or collectively, we find that collectively behaving bugs tend to align, which results in relatively more cohesive groups. In addition, cohesion among bats is induced since bats may be attracted to the same localized bug group. Due to the fact that bats need to hunt more widely for groups of bugs, collectively behaving bugs suffer less predation compared to their randomly swarming counterparts. These findings are supported by the biological literature which cites protection from predation as a primary motivator for social behavior.

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Multi-Agent Systems in Three-Dimensional Protein Structure Prediction

Biotechnology ◽

10.4018/978-1-5225-8903-7.ch040 ◽

2019 ◽

pp. 1031-1068

Author(s):

Leonardo de Lima Corrêa ◽

Márcio Dorn

Keyword(s):

Protein Structure ◽

Protein Structure Prediction ◽

Structure Prediction ◽

Protein Structures ◽

Three Dimensional ◽

Multi Agent Systems ◽

Agent Based ◽

Agent Systems ◽

Tertiary Protein Structure ◽

Multi Agent

Tertiary protein structure prediction in silico is currently a challenging problem in Structural Bioinformatics and can be classified according to the computational complexity theory as an NP-hard problem. Determining the 3-D structure of a protein is both experimentally expensive, and time-consuming. The agent-based paradigm has been shown a useful technique for the applications that have repetitive and time-consuming activities, knowledge share and management, such as integration of different knowledge sources and modeling of complex systems, supporting a great variety of domains. This chapter provides an integrated view and insights about the protein structure prediction area concerned to the usage, application and implementation of multi-agent systems to predict the protein structures or to support and coordinate the existing predictors, as well as it is advantages, issues, needs, and demands. It is noteworthy that there is a great need for works related to multi-agent and agent-based paradigms applied to the problem due to their excellent suitability to the problem.

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EVACUATION SIMULATION IN KALAYAAN RESIDENCE HALL, UP DILIMAN USING GAMA SIMULATION SOFTWARE

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w1-83-2016 ◽

2016 ◽

Vol XLII-4/W1 ◽

pp. 83-87

Author(s):

A. R. C. Claridades ◽

J. K. S. Villanueva ◽

E. G. Macatulad

Keyword(s):

Demographic Data ◽

Three Dimensional ◽

Scientific Basis ◽

Residence Hall ◽

Simulation Software ◽

Evacuation Simulation ◽

Evacuation Time ◽

Agent Based ◽

Multi Agent ◽

Floor Plans

Agent-Based Modeling (ABM) has recently been adopted in some studies for the modelling of events as a dynamic system given a set of events and parameters. In principle, ABM employs individual agents with assigned attributes and behaviors and simulates their behavior around their environment and interaction with other agents. This can be a useful tool in both micro and macroscale-applications. In this study, a model initially created and applied to an academic building was implemented in a dormitory. In particular, this research integrates three-dimensional Geographic Information System (GIS) with GAMA as the multi-agent based evacuation simulation and is implemented in Kalayaan Residence Hall. A three-dimensional GIS model is created based on the floor plans and demographic data of the dorm, including respective pathways as networks, rooms, floors, exits and appropriate attributes. This model is then re-implemented in GAMA. Different states of the agents and their effect on their evacuation time were then observed. GAMA simulation with varying path width was also implemented. It has been found out that compared to their original states, panic, eating and studying will hasten evacuation, and on the other hand, sleeping and being on the bathrooms will be impedances. It is also concluded that evacuation time will be halved when path widths are doubled, however it is recommended for further studies for pathways to be modeled as spaces instead of lines. A more scientific basis for predicting agent behavior in these states is also recommended for more realistic results.

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