An agent-based framework for selection of partners in dynamic virtual enterprises

Advances in computer networking technology and open system standards have made practically feasible to create and manage virtual enterprises. A virtual enterprise, VE, is usually defined as a temporary alliance of enterprises that come together to share their skills, core competencies, and resources in order to better respond to business opportunities, and whose cooperation is supported by computer networks. The materialization of this paradigm, although enabled by recent advances in communication technologies, computer networks and logistics, requires an appropriate architectural framework and support tools. In this paper we propose an agent-based model of a dynamic VE to support the different selection processes that are used in selecting the partners for a dynamic VE, where the partners of a VE are represented by agents. Such a framework will form the basis for tools that provide automated support for creation, and operation, of dynamic virtual enterprises

Towards engineering ontologies for cognitive profiling of agents on the semantic web

Research shows that most agent-based collaborations suffer from lack of flexibility. This is due to the fact that most agent-based applications assume pre-defined knowledge of agents’ capabilities and/or neglect basic cognitive and interactional requirements in multi-agent collaboration. The highlight of this paper is that it brings cognitive models (inspired from cognitive sciences and HCI) proposing architectural and knowledge-based requirements for agents to structure ontological models for cognitive profiling in order to increase cognitive awareness between themselves, which in turn promotes flexibility, reusability and predictability of agent behavior; thus contributing towards minimizing cognitive overload incurred on humans. The semantic web is used as an action mediating space, where shared knowledge base in the form of ontological models provides affordances for improving cognitive awareness

Multi-Agent System Interaction in Integrated SCM\ud

Coordination between organizations on strategic, tactical and operation levels leads to more effective and efficient supply chains. Supply chain management is increasing day by day in modern enterprises.. The environment is becoming competitive and many enterprises will find it difficult to survive if they do not make their sourcing, production and distribution more efficient. Multi-agent supply chain management has recognized as an effective methodology for supply chain management. Multi-agent systems (MAS) offer new methods compared to conventional, centrally organized architectures in the scope of supply chain management (SCM). Since necessary data are not available within the whole supply chain, an integrated approach for production planning and control taking into account all the partners involved is not feasible. In this study we show how MAS architecture interacts in the integrated SCM architecture with the help of various intelligent agents to highlight the above problem

Preliminary specification and design documentation for software components to achieve catallaxy in computational systems

This Report is about the preliminary specifications and design documentation for software components to achieve Catallaxy in computational systems. -- Die Arbeit beschreibt die Spezifikation und das Design von Softwarekomponenten, um das Konzept der Katallaxie in Grid Systemen umzusetzen. Eine Einführung ordnet das Konzept der Katallaxie in bestehende Grid Taxonomien ein und stellt grundlegende Komponenten vor. Anschließend werden diese Komponenten auf ihre Anwendbarkeit in bestehenden Application Layer Netzwerken untersucht.Grid Computing

A Review on Intelligent Agent Systems

Multi-agent system (MAS) is a common way of exploiting the potential power of agent by combining many agents in one system. Each agent in a multivalent system has incomplete information and is in capable of solving entire problem on its own. Multi-agent system offers modularity. If a problem domain is particularly complex, large and contain uncertainty, then the one way to address, it to develop a number of functional specific and modular agent that are specialized at solving various problems individually. It also consists of heterogeneous agents implemented by different tool and techniques. MAS can be defining as loosely coupled network of problem solvers that interact to solve problems that are beyond the individual capabilities or knowledge of each problem solver. These problem solvers, often ailed agent are autonomous and can be heterogeneous in nature. MAS is followed by characteristics, Future application, What to be change, problem solving agent, tools and techniques used, various architecture, multi agent applications and finally future Direction and conclusion. Various Characteristics are limited viewpoint, effectively, decentralized; computation is asynchronous, use of genetic algorithms. It has some drawbacks which must be change to make MAS more effective. In the session of problem solving of MAS, the agent performance measure contains many factors to improve it like formulation of problems, task allocation, organizations. In planning of multivalent this paper cover self-interested multivalent interactions, modeling of other agents, managing communication, effective allocation of limited resources to multiple agents with managing resources. Using of tool, to make the agent more efficient in task that are often used. The architecture o MAS followed by three layers, explore, wander, avoid obstacles respectively. Further different and task decomposition can yield various architecture like BDI (Belief Desire Intension), RETSINA. Various applications of multi agent system exist today, to solve the real-life problems, new systems are being developed two distinct categories and also many others like process control, telecommunication, air traffic control, transportation systems, commercial management, electronic commerce, entertainment applications, medical applications. The future aspect of MAS to solve problems that are too large, to allow interconnection and interoperation of multiple existing legacy systems etc

Human Computer Interactions in Next-Generation of Aircraft Smart Navigation Management Systems: Task Analysis and Architecture under an Agent-Oriented Methodological Approach

The limited efficiency of current air traffic systems will require a next-generation of Smart Air Traffic System (SATS) that relies on current technological advances. This challenge means a transition toward a new navigation and air-traffic procedures paradigm, where pilots and air traffic controllers perform and coordinate their activities according to new roles and technological supports. The design of new Human-Computer Interactions (HCI) for performing these activities is a key element of SATS. However efforts for developing such tools need to be inspired on a parallel characterization of hypothetical air traffic scenarios compatible with current ones. This paper is focused on airborne HCI into SATS where cockpit inputs came from aircraft navigation systems, surrounding traffic situation, controllers' indications, etc. So the HCI is intended to enhance situation awareness and decision-making through pilot cockpit. This work approach considers SATS as a system distributed on a large-scale with uncertainty in a dynamic environment. Therefore, a multi-agent systems based approach is well suited for modeling such an environment. We demonstrate that current methodologies for designing multi-agent systems are a useful tool to characterize HCI. We specifically illustrate how the selected methodological approach provides enough guidelines to obtain a cockpit HCI design that complies with future SATS specifications.This work was supported in part by Projects MINECO TEC2011-28626-C02-01/02, by program CENIT-ATLANTIDA (cofinanced by Indra and Boeing R&TE), and by ULPGC Precompetitive Research Project (ULPGC Own Program).Publicad