Applying Situated Agents to Microscopic Traffic Modelling

2009 ◽  
pp. 108-123 ◽  
Author(s):  
Paulo A.F. Ferreira ◽  
Edgar F. Esteves ◽  
Rosaldo J.F. Rossetti ◽  
Eugénio C. Oliveira
Keyword(s):  
Cognitive Abilities ◽  
Communication Model ◽  
Microscopic Traffic Simulation ◽  
Change Models ◽  
Agent Model ◽  
Car Following ◽  
Microscopic Models ◽  
Realistic Representation ◽  
Multi Agent

Trading off between realism and too much abstraction is an important issue to address in microscopic traffic simulation. In this chapter the authors bring this discussion forward and propose a multi-agent model of the traffic domain where integration is ascribed to the way the environment is represented and agents interoperate. While most approaches still deal with drivers and vehicles indistinguishably, in the proposed framework vehicles are merely moveable objects whereas the driving role is played by agents fully endowed with cognitive abilities and situated in the environment. The authors discuss on the role of the environment dynamics in supporting a truly emergent behaviour of the system and present an extension to the traditional car-following and lane-change models based on the concept of situated agents. A physical communication model is proposed to base different interactions and some performance issues are also identified, which allows for more realistic representation of drivers’ behaviour in microscopic models.

An Ontological Approach to Managing Project Memories in Organizations

2011 ◽  
pp. 233-261 ◽  
Author(s):  
Davy Monticolo ◽  
Vincent Hilaire ◽  
Samuel Gomes ◽  
Abderrafiaa Koukam
Keyword(s):  
Mechanical Design ◽  
Domain Ontology ◽  
Organizational Memory ◽  
Knowledge Modeling ◽  
Distributed Knowledge ◽  
Agent Model ◽  
Professional Activities ◽  
Ontological Approach ◽  
Multi Agent

Knowledge Management (KM) is considered by many organizations a key aspect in sustaining competitive advantage. In the mechanical design domain, the KM facilitates the design of routine product and brings a saving time for innovation. This chapter describes the specification of a project memory as an organizational memory to specify knowledge to capitalize all along project in order to be reuse. Afterwards it presents the design of a domain ontology and a multi agent system to manage project memories all along professional activities. As a matter of fact, these activities require that engineers, with different specialities, collaborate to carry out the same goal. Inside professional activities; they use their knowhow and knowledge in order to achieve the laid down goals. The professional actors competences and knowledge modeling allows the design and the description of agents’ know-how. Furthermore, the paper describes the design of our agent model based on an organisational approach and the role of a domain ontology called OntoDesign to manage heterogeneous and distributed knowledge.

An Ontological Approach to Managing Project Memories in Organizations

2009 ◽  
pp. 244-269 ◽  
Author(s):  
Davy Monticolo ◽  
Vincent Hilaire ◽  
Samuel Gomes ◽  
Abderrafiaa Koukam
Keyword(s):  
Mechanical Design ◽  
Domain Ontology ◽  
Organizational Memory ◽  
Knowledge Modeling ◽  
Distributed Knowledge ◽  
Agent Model ◽  
Professional Activities ◽  
Ontological Approach ◽  
Multi Agent

Knowledge Management (KM) is considered by many organizations a key aspect in sustaining competitive advantage. In the mechanical design domain, the KM facilitates the design of routine product and brings a saving time for innovation. This chapter describes the specification of a project memory as an organizational memory to specify knowledge to capitalize all along project in order to be reuse. Afterwards it presents the design of a domain ontology and a multi agent system to manage project memories all along professional activities. As a matter of fact, these activities require that engineers, with different specialities, collaborate to carry out the same goal. Inside professional activities; they use their knowhow and knowledge in order to achieve the laid down goals. The professional actors competences and knowledge modeling allows the design and the description of agents’ know-how. Furthermore, the paper describes the design of our agent model based on an organisational approach and the role of a domain ontology called OntoDesign to manage heterogeneous and distributed knowledge.

Ignition of Algorithm Mind

2017 ◽  
pp. 1-24
Author(s):  
Nuno Trindade Magessi ◽  
Luis Antunes
Keyword(s):  
Complex Structure ◽  
Ignition Process ◽  
Recruitment Process ◽  
Agent Model ◽  
Neuronal Assemblies ◽  
Multi Agent

The ignition of the algorithmic mind is a fascinating phenomenon that occurs in our brains. The algorithm mind is related to our reasoning. When we use it, we consume a lot of resources from our brains like energy. The ignition process is triggered by reflective mind and it works through neuronal assemblies. Specific neurons are ignited and then it begins a recruitment process for other neurons in order to assemble a complex structure. To understand these mechanisms, we have developed a simple multi-agent model, where we explored the role of energy and respective limits on neuronal assemblies. The available and consumed energy are the keystones to ignite the algorithm mind and to find out the limit that interrupts our reasoning's. The connections between incumbent and new neurons are at the same level as the connections established only between the new neurons in the case of algorithmic mind. Unlike, the autonomous mind established more connections, only between new neurons. Finally, the algorithmic mind consumes more energy than autonomous mind, which has a clearly declining trend.

Role of Non-Traditional Machining Equipment in Industry 4.0

2021 ◽  
pp. 203-214
Author(s):  
Tarun Kanti Jana
Keyword(s):  
Cognitive Abilities ◽  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Dynamic Capabilities ◽  
Low Cost ◽  
Human Beings ◽  
Agent Based ◽  
Multi Agent ◽  
Conventional Machining

The manufacturing industry is undergoing drastic changes owing to a steep rise in business competition and growing complexities in other business perspectives. The highly turbulent market is characterized by ever-increasing mass customization, wide volume-mix, shorter lead time, and low cost, which along with varieties of internal disturbances have complicated the business stability. The multi-agent-based systems comprising of fundamental entities called agents and characterized by autonomy, cooperation, and self-organizing abilities have already made remarkable breakthrough to deal with the challenges through increased robustness, scalability, and enhanced adaptability through their dynamic capabilities. The decision-making ability of the agents can be augmented if equipped with cognitive abilities like that of human beings. The chapter discusses cyber-physical production system (CPPS) to realize cognitive manufacturing in non-conventional machining environments.

The Agent-Oriented Methodology MAS-CommonKADS

2011 ◽  
pp. 445-468 ◽  
Author(s):  
Carlos A. Iglesias ◽  
Mercedes Garijo
Keyword(s):  
Knowledge Engineering ◽  
Object Oriented ◽  
Design Model ◽  
Communication Model ◽  
Multi Agent Systems ◽  
Agent Model ◽  
Agent Systems ◽  
Coordination Model ◽  
Multi Agent ◽  
Generic Component

This chapter introduces the main concepts of the methodology MAS-CommonKADS that extends object-oriented and knowledge engineering techniques for the conceptualisation of multi-agent systems. MAS-CommonKADS defines a set of models (Agent Model, Task Model, Expertise Model, Coordination Model, Communication Model, Organisation Model, and Design Model) that together provide a model of the problem to be solved. Each of the components of the model is a generic component for the sake of reusability. Readers familiar with object-oriented analysis will find it easy to apply most of the techniques of MAS-CommonKADS in the development of multi-agent systems and will be introduced to the application of knowledge engineering techniques for specifying the knowledge of the agents.

scholarly journals An Automatic Calibration Procedure of Driving Behaviour Parameters in the Presence of High Bus Volume

2019 ◽  
Vol 31 (5) ◽  
pp. 491-502 ◽  
Author(s):  
Nima Dadashzadeh ◽  
Murat Ergun ◽  
Sercan Kesten ◽  
Marijan Žura
Keyword(s):  
Calibration Procedure ◽  
Automatic Calibration ◽  
Traffic Data ◽  
Microscopic Traffic Simulation ◽  
Change Models ◽  
Calibration Process ◽  
Car Following ◽  
Driving Behaviour ◽  
Optimization Stage ◽  
Behaviour Models

Most of the microscopic traffic simulation programs used today incorporate car-following and lane-change models to simulate driving behaviour across a given area. The main goal of this study has been to develop an automatic calibration process for the parameters of driving behaviour models using metaheuristic algorithms. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a combination of GA and PSO (i.e. hybrid GAPSO and hybrid PSOGA) were used during the optimization stage. In order to verify our proposed methodology, a suitable study area with high bus volume on-ramp from the O-1 Highway in Istanbul has been modelled in VISSIM. Traffic data have been gathered through detectors. The calibration procedure has been coded using MATLAB and implemented via the VISSIM-MATLAB COM interface. Using the proposed methodology, the results of the calibrated model showed that hybrid GAPSO and hybrid PSOGA techniques outperformed the GA-only and PSO-only techniques during the calibration process. Thus, both are recommended for use in the calibration of microsimulation traffic models, rather than GA-only and PSO-only techniques.

scholarly journals Local operators in kinetic wealth distribution

2016 ◽  
Vol 27 (11) ◽  
pp. 1650132
Author(s):  
M. Andrecut
Keyword(s):  
Wealth Distribution ◽  
Particle Scattering ◽  
Scattering Process ◽  
Agent Model ◽  
Multi Agent ◽  
Local Operators ◽  
Elastic Particle ◽  
Fine Tune ◽  
Interaction Rule

The statistical mechanics approach to wealth distribution is based on the conservative kinetic multi-agent model for money exchange, where the local interaction rule between the agents is analogous to the elastic particle scattering process. Here, we discuss the role of a class of conservative local operators, and we show that, depending on the values of their parameters, they can be used to generate all the relevant distributions. We also show numerically that in order to generate the power-law tail, an heterogeneous risk aversion model is required. By changing the parameters of these operators, one can also fine tune the resulting distributions in order to provide support for the emergence of a more egalitarian wealth distribution.

The Agent-Oriented Methodology MAS-CommonKADS

2011 ◽  
pp. 46-78 ◽  
Author(s):  
Carlos A. Iglesias ◽  
Mercedes Garijo
Keyword(s):  
Knowledge Engineering ◽  
Object Oriented ◽  
Design Model ◽  
Communication Model ◽  
Multi Agent Systems ◽  
Agent Model ◽  
Agent Systems ◽  
Coordination Model ◽  
Multi Agent ◽  
Generic Component

This chapter introduces the main concepts of the methodology MAS-CommonKADS that extends object-oriented and knowledge engineering techniques for the conceptualisation of multi-agent systems. MAS-CommonKADS defines a set of models (Agent Model, Task Model, Expertise Model, Coordination Model, Communication Model, Organisation Model, and Design Model) that together provide a model of the problem to be solved. Each of the components of the model is a generic component for the sake of reusability. Readers familiar with object-oriented analysis will find it easy to apply most of the techniques of MAS-CommonKADS in the development of multi-agent systems and will be introduced to the application of knowledge engineering techniques for specifying the knowledge of the agents.

Refining our understanding of the “elephant in the room”

2020 ◽  
Vol 43 ◽  
Author(s):  
Andrew Whiten
Keyword(s):  
Social Cognition ◽  
Cultural Evolution ◽  
Cognitive Abilities ◽  
Critical Factors ◽  
Technological Culture

Abstract The authors do the field of cultural evolution a service by exploring the role of non-social cognition in human cumulative technological culture, truly neglected in comparison with socio-cognitive abilities frequently assumed to be the primary drivers. Some specifics of their delineation of the critical factors are problematic, however. I highlight recent chimpanzee–human comparative findings that should help refine such analyses.

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