scholarly journals AiD-EM: Adaptive Decision Support for Electricity Markets Negotiations

2019 ◽  
Author(s):  
Tiago Pinto ◽  
Zita Vale
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Support ◽  
Electricity Markets ◽  
Evolutionary Computing ◽  
Multi Agent System ◽  
Agent System ◽  
Agent Based ◽  
Multi Agent ◽  
Competitive Electricity Markets

This paper presents the Adaptive Decision Support for Electricity Markets Negotiations (AiD-EM) system. AiD-EM is a multi-agent system that provides decision support to market players by incorporating multiple sub-(agent-based) systems, directed to the decision support of specific problems. These sub-systems make use of different artificial intelligence methodologies, such as machine learning and evolutionary computing, to enable players adaptation in the planning phase and in actual negotiations in auction-based markets and bilateral negotiations. AiD-EM demonstration is enabled by its connection to MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

scholarly journals Fine Tuning of Agent-Based Evolutionary Computing

2019 ◽  
Vol 9 (2) ◽  
pp. 81-97 ◽  
Author(s):  
Michal Mizera ◽  
Pawel Nowotarski ◽  
Aleksander Byrski ◽  
Marek Kisiel-Dorohinicki
Keyword(s):  
Science And Technology ◽  
Evolutionary Computing ◽  
Fine Tuning ◽  
High Dimensional ◽  
Multi Agent System ◽  
Agent System ◽  
Agent Based ◽  
Optimization System ◽  
Computing Algorithm ◽  
Multi Agent

Abstract Evolutionary Multi-agent System introduced by late Krzysztof Cetnarowicz and developed further at the AGH University of Science and Technology became a reliable optimization system, both proven experimentally and theoretically. This paper follows a work of Byrski further testing and analyzing the efficacy of this metaheuristic based on popular, high-dimensional benchmark functions. The contents of this paper will be useful for anybody willing to apply this computing algorithm to continuous and not only optimization.

scholarly journals A multi-agent-based approach for address geocoding in poorly mapped areas through public company data

2021 ◽  
Vol 3 (1) ◽  
pp. 1-9
Author(s):  
Mouhamad Al Mansour KEBE ◽  
Roger Marcelin FAYE ◽  
Claude LISHOU
Keyword(s):  
Current Knowledge ◽  
Original Method ◽  
Local Context ◽  
Multi Agent System ◽  
Industrialized Countries ◽  
Agent System ◽  
Agent Based ◽  
Public Company ◽  
Spatial Coordinates ◽  
Multi Agent

In this study, we present an original method that enhances geocoding systems in poorly mapped areas thanks to public company data and a multi-agent system. In contrast with industrialized countries, many developing countries lack formal postal address systems assignments and usage, making the operation of translating text-based addresses to absolute spatial coordinates, known as geocoding, a big challenge. We recreated a standard of address as it is perceived and used by local people, a kind of non-official national address standard since there is no official one in these areas. Then, we designed a multi-agent system in which agents are assigned different tasks of geocoding process and can perform negotiation to achieve a global objective: find the best possible match or approximation of a location-based on current knowledge. Verification of the usefulness of the proposed approach is made in comparison with Google Geocoding API which shows that the proposed approach has great potential to geocode addresses considering local context semantic issues.

Determination of Factors Affecting Safety Stress in Machine Design by Using Artificial Intelligence Technologies

2008 ◽  
Vol 144 ◽  
pp. 232-237
Author(s):  
Durmus Karayel ◽  
Sinan Serdar Ozkan ◽  
Fahri Vatansever
Keyword(s):  
Artificial Intelligence ◽  
Information Technologies ◽  
Intelligent System ◽  
System Model ◽  
Multi Agent System ◽  
Safety Factors ◽  
Agent System ◽  
Factors Affecting ◽  
Classical Design ◽  
Multi Agent

In this study, an intelligent system model that can evaluate experimental material properties and safety factors is developed. The model contains Artificial Intelligence Technologies such as Artificial Neural Network (ANN) and Fuzzy Logic. It consists of sub modules into interaction. Also, the model can obtain more precision values than interpolation techniques used to classical design. The study contributes to define safety factors, design criterions and safety stress according to a new approach based on information technologies. So, this study can be seen as one of the sub modules of Intelligence Multi Agent System and it can be integrated with Multi Agent System Model for design. Also, it can be used for classical design studies so that results can be quickly obtained. It is expected that this approach will be widely used by designers.

A Clustering Approach Based on Cooperative Agents to Improve Decision Support in ERP

2019 ◽  
pp. 1-18
Author(s):  
Nadjib Mesbahi ◽  
Okba Kazar ◽  
Saber Benharzallah ◽  
Merouane Zoubeidi ◽  
Djamil Rezki
Keyword(s):  
Decision Support ◽  
Intelligent Systems ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Cooperative Agents ◽  
Distributed Problem Solving ◽  
Multi Agent ◽  
Complete Set ◽  
Clustering Approach

Multi-agent systems (MAS) are a powerful technology for the design and implementation of autonomous intelligent systems that can handle distributed problem solving in a complex environment. This technology has played an important role in the development of data mining systems in the last decade, the purpose of which is to promote the extraction of information and knowledge from a large database and to make these systems more scalable. In this chapter, the authors present a clustering system based on cooperative agents through a centralized and common ERP database to improve decision support in ERP systems. To achieve this, they use multi-agent system paradigm to distribute the complexity of k-means algorithm in several autonomous entities called agents, whose goal is to group records or observations on similar objects classes. This will help business decision makers to make good decisions and provide a very good response time by the use of the multi-agent system. To implement the proposed architecture, it is more convenient to use the JADE platform while providing a complete set of services and have agents comply with the specifications FIPA.

Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems

2011 ◽  
pp. 118-136 ◽  
Author(s):  
Robert E. Smith ◽  
Claudio Bonacina
Keyword(s):  
Evolutionary Computation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Future Directions ◽  
Agent Based ◽  
Agent Systems ◽  
Emergent Behaviour ◽  
Shaping System ◽  
Multi Agent

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.

Agent-Based Infrastructure for Dynamic Composition of Grid Services

2010 ◽  
pp. 911-936
Author(s):  
Matthew Adigun ◽  
Johnson Iyilade ◽  
Klaas Kabini
Keyword(s):  
Service Composition ◽  
Research Effort ◽  
Multi Agent System ◽  
Grid Services ◽  
Agent System ◽  
Agent Based ◽  
Dynamic Composition ◽  
Emerging Trends ◽  
Dynamic Service Composition ◽  
Multi Agent

The service-oriented computing paradigm is based on the assumption that existing services can be put together in order to obtain new composite services. This chapter focuses on how peer-to-peer architectures based on multi-agent systems can be used to build highly dynamic and reconfigurable infrastructure that support dynamic composition of grid services. The chapter starts by providing an overview of key technologies for SOC. It then introduces dynamic service composition and challenges of composing grid services. The authors further motivate for Multi-agent system approach in SOC and why it becomes important in service composition. They then present our research effort, AIDSEC, an agent-based infrastructure for dynamic service composition, describing its architecture, implementation and comparison with some related work in the literature. In addition, the chapter raises some emerging trends in SOC and the particular challenges they pose to service composition. They conclude by suggesting that a solution based on multi-agent system is required for composing services that possess capabilities of autonomy, reliability, flexibility, and robustness.

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