An Ontological Approach to Managing Project Memories in Organizations

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.

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Developing a multi-agent model for distributed knowledge systems

Proceedings of International Conference on Expert Systems for Development ◽

10.1109/icesd.1994.302307 ◽

2002 ◽

Author(s):

D. Cho ◽

F. Kusunoki ◽

S. Ono ◽

T. Terano

Keyword(s):

Knowledge Systems ◽

Distributed Knowledge ◽

Agent Model ◽

Multi Agent ◽

Distributed Knowledge Systems

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Applying Situated Agents to Microscopic Traffic Modelling

Multi-Agent Systems for Traffic and Transportation Engineering - Advances in Mechatronics and Mechanical Engineering ◽

10.4018/978-1-60566-226-8.ch005 ◽

2009 ◽

pp. 108-123 ◽

Cited By ~ 3

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.

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A multi agent model to support the knowledge management process inside professional activities

2007 2nd International Conference on Digital Information Management ◽

10.1109/icdim.2007.4444322 ◽

2007 ◽

Cited By ~ 1

Author(s):

Davy Monticolo ◽

Vincent Hilaire ◽

Abder Koukam ◽

Samuel Gomes

Keyword(s):

Knowledge Management ◽

Management Process ◽

Agent Model ◽

Professional Activities ◽

Multi Agent

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Ignition of Algorithm Mind

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

10.4018/978-1-5225-1756-6.ch001 ◽

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.

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Local operators in kinetic wealth distribution

International Journal of Modern Physics C ◽

10.1142/s0129183116501321 ◽

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.

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THE ROLE OF LAW ENFORCEMENT AGENCIES IN ENSURING THE PRINCIPLE OF LEGALITY DURING THE GREAT PATRIOTIC WAR

Law and law: problems of theory and practice ◽

10.29039/02033-3/013-018 ◽

2020 ◽

Author(s):

Ruslan Ahmedov ◽

Yuliya Ivanova

Keyword(s):

Law Enforcement ◽

Law Enforcement Officers ◽

75Th Anniversary ◽

Law Enforcement Agencies ◽

Professional Activities ◽

Soviet People ◽

Great Patriotic War ◽

Principle Of Legality

In 2020, the 75th anniversary of the Victory of the soviet people is celebrated over fascism. An important role in achieving this result in the conditions law enforcement officers also provided wartime assistance. The main purpose of their professional activities was to ensure the implementation of principles of legality.

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