Chaotic multiagent system approach for MRF-based image segmentation

2005 ◽  
Author(s):  
K.E. Melkemi ◽  
M. Batouche ◽  
S. Foufou
Keyword(s):  
Image Segmentation ◽  
System Approach ◽  
Multiagent System

Performance of Gas Turbine Power Plants Controlled by Multiagent Scheme

2006 ◽  
Author(s):  
Lorenzo Dambrosio ◽  
Marco Mastrovito ◽  
Sergio M. Camporeale
Keyword(s):  
Artificial Intelligence ◽  
Gas Turbine ◽  
System Approach ◽  
Power Plants ◽  
Multiagent System ◽  
Control Process ◽  
Control Algorithms ◽  
Load Reduction ◽  
Heavy Duty ◽  
Heavy Duty Gas Turbine

In latter years the idea of artificial intelligence has been focused around the concept of a rational agent. An agent is a (software or hardware) entity that can receive signals from the environment and act upon that environment through output signals. In general an agent always tries to carry out an appropriate task. Seldom agents are considered as stand-alone systems. Their main strength can be found in the interaction with other agents in several different ways in a multiagent system. In the present work, multiagent system approach will be used to manage the control process of a single-shaft heavy-duty gas turbine in Multi Input Multi Output mode. The results will show that the multiagent approach to the control problem effectively counteracts the load reduction (including the load rejection condition) with limited overshoot in the controlled variables (as other control algorithms do) while showing good level adaptivity readiness, precision, robustness and stability.

Intelligent Local Energy Communities: A Multiagent System Approach

2021 ◽  
pp. 26-51
Author(s):  
Roman Denysiuk ◽  
Fabio Lilliu ◽  
Meritxell Vinyals ◽  
Diego Reforgiato Recupero
Keyword(s):  
System Approach ◽  
Multiagent System ◽  
Local Energy

Cooperation Between Agents to Evolve Complete Programs

2011 ◽  
pp. 213-228 ◽  
Author(s):  
Ricardo Aler ◽  
David Camacho ◽  
Alfredo Moscardini
Keyword(s):  
Genetic Programming ◽  
Computer Program ◽  
System Approach ◽  
Multiagent System ◽  
Computer Programs ◽  
Main Body ◽  
Programming Paradigm

In this paper, we present a multiagent system approach with the purpose of building computer programs. Each agent in the multiagent system will be in charge of evolving a part of the program, which in this case, can be the main body of the program or one of its different subroutines. There are two kinds of agents: the manager agent and the genetic programming (GP) agents. The former is in charge of starting the system and returning the results to the user. The GP agents include skills for evolving computer programs, based on the genetic programming paradigm. There are two sorts of GP agents: some can evolve the main body of the program and the others evolve its subroutines. Both kinds of agents cooperate by telling each other their best results found so far, so that the search for a good computer program is made more efficient. In this paper, this multiagent approach is presented and tested empirically.

Sign in / Sign up

Export Citation Format

Share Document