On the Identification of Agents in the Design of Production Control Systems

This paper describes a methodology that is being developed for designing and building agent-based systems for the domain of production control. In particular, this paper deals with the steps that are involved in identifying the agents and in specifying their responsibilities. The methodology aims to be usable by engineers who have a background in production control but who have no prior experience in agent technology. For this reason, the methodology needs to be very prescriptive with respect to the agent-related aspects of design

KEMNAD: A Knowledge Engineering Methodology for Negotiating Agent Development

Automated negotiation is widely applied in various domains. However, the development of such systems is a complex knowledge and software engineering task. So, a methodology there will be helpful. Unfortunately, none of existing methodologies can offer sufficient, detailed support for such system development. To remove this limitation, this paper develops a new methodology made up of: (1) a generic framework (architectural pattern) for the main task, and (2) a library of modular and reusable design pattern (templates) of subtasks. Thus, it is much easier to build a negotiating agent by assembling these standardised components rather than reinventing the wheel each time. Moreover, since these patterns are identified from a wide variety of existing negotiating agents(especially high impact ones), they can also improve the quality of the final systems developed. In addition, our methodology reveals what types of domain knowledge need to be input into the negotiating agents. This in turn provides a basis for developing techniques to acquire the domain knowledge from human users. This is important because negotiation agents act faithfully on the behalf of their human users and thus the relevant domain knowledge must be acquired from the human users. Finally, our methodology is validated with one high impact system

A framework for knowledge discovery within business intelligence for decision support

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Business Intelligence (BI) techniques provide the potential to not only efficiently manage but further analyse and apply the collected information in an effective manner. Benefiting from research both within industry and academia, BI provides functionality for accessing, cleansing, transforming, analysing and reporting organisational datasets. This provides further opportunities for the data to be explored and assist organisations in the discovery of correlations, trends and patterns that exist hidden within the data. This hidden information can be employed to provide an insight into opportunities to make an organisation more competitive by allowing manager to make more informed decisions and as a result, corporate resources optimally utilised. This potential insight provides organisations with an unrivalled opportunity to remain abreast of market trends. Consequently, BI techniques provide significant opportunity for integration with Decision Support Systems (DSS). The gap which was identified within the current body of knowledge and motivated this research, revealed that currently no suitable framework for BI, which can be applied at a meta-level and is therefore tool, technology and domain independent, currently exists. To address the identified gap this study proposes a meta-level framework: - ‘KDDS-BI’, which can be applied at an abstract level and therefore structure a BI investigation, irrespective of the end user. KDDS-BI not only facilitates the selection of suitable techniques for BI investigations, reducing the reliance upon ad-hoc investigative approaches which rely upon ‘trial and error’, yet further integrates Knowledge Management (KM) principles to ensure the retention and transfer of knowledge due to a structured approach to provide DSS that are based upon the principles of BI. In order to evaluate and validate the framework, KDDS-BI has been investigated through three distinct case studies. First KDDS-BI facilitates the integration of BI within ‘Direct Marketing’ to provide innovative solutions for analysis based upon the most suitable BI technique. Secondly, KDDS-BI is investigated within sales promotion, to facilitate the selection of tools and techniques for more focused in store marketing campaigns and increase revenue through the discovery of hidden data, and finally, operations management is analysed within a highly dynamic and unstructured environment of the London Underground Ltd. network through unique a BI solution to organise and manage resources, thereby increasing the efficiency of business processes. The three case studies provide insight into not only how KDDS-BI provides structure to the integration of BI within business process, but additionally the opportunity to analyse the performance of KDDS-BI within three independent environments for distinct purposes provided structure through KDDS-BI thereby validating and corroborating the proposed framework and adding value to business processes

An ontology-based representation of an agent-based controlled robotic cell

Dissertação apresentada na Faculdade de Ciência e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de ComputadoresCustomers demand for high product customization and differentiation, and short product life-cycle. As such, industries have to adapt their manufacturing systems more frequently in order to remain competitive. Changing manufacturing systems within a short period of time requires a huge effort in terms of time and money, reducing this effort would make industries more competitive. The proposed solution consists in developing an ontology-based multi-agent system to control manufacturing systems. Defining the ontology for the manufacturing system allows the control to perform its operation, and when changes arise, it is required to change the ontology so that the control became aware of the changes to control the manufacturing system. An ontology-based control allows for a smaller setup time since the control is not specific for one physical system and can be applied to different ones, therefore it reduces the effort in adapting manufacturing systems to required changes allowing industries to became more competitive. Flexibility is given by the multi-agent system that controls the physical system with the ontology. Stating this, the solution of an ontology-based control for manufacturing systems provides the required results

Flexible Decision Control in an Autonomous Trading Agent

An autonomous trading agent is a complex piece of software that must operate in a competitive economic environment and support a research agenda. We describe the structure of decision processes in the MinneTAC trading agent, focusing on the use of evaluators – configurable, composable modules for data analysis and prediction that are chained together at runtime to support agent decision-making. Through a set of examples, we show how this structure supports sales and procurement decisions, and how those decision processes can be modified in useful ways by changing evaluator configurations. To put this work in context, we also report on results of an informal survey of agent design approaches among the competitors in the Trading Agent Competition for Supply Chain Management (TAC SCM).autonomous trading agent;decision processes

Intelligent Agents as a Modeling Paradigm

Intelligent software agents have been used in many applications because they provide useful integrated features that are not available in “traditional” types of software (e.g., abilities to sense the environment, reason, and interact with other agents). Although the usefulness of agents is in having such capabilities, methods and tools for developing them have focused on practical physical representation rather than accurate conceptualizations of these functions. However, intelligent agents should closely mimic aspects of the environment in which they operate. In the physical sciences, a conceptual model of a problem can lead to better theories and explanations about the area. Therefore, we ask, can an intelligent agent conceptual framework, properly defined, be used to model complex interactions in various social science disciplines? The constructs used in the implementation of intelligent agents may not be appropriate at the conceptual level, as they refer to software concepts rather than to application domain concepts. We propose to use a combina- tion of the systems approach and Bunge’s ontology as adapted to information systems, to guide us in defining intelligent agent concepts. The systems approach will be used to define the components of the intelligent agents and ontology will be used to understand the configurations and interrelationships between the components. We will then provide a graphical representation of these concepts for modeling purposes. As a proof of concept for the proposed conceptual model, we applied it to a marketing problem and imple- mented it in an agent-based programming environment. Using the conceptual model, the user was able to quickly visualize the complex interactions of the agents. The use of the conceptual representation even sparked an investigation of previously neglected causal factors which led to a better understanding of the problem. Therefore, our intelligent agent framework can graphically model phenomena in the social sciences. This work also provides a theoretically driven concept of intelligent agent components and a definition of the inter- relationships between these concepts. Further research avenues are also discussed

Requirements Modeling for Multi-Agent Systems

Different approaches for building modern software systems in complex and open environments have been proposed in the last few years. Some efforts try to take advantage of the agent-oriented paradigm to model/engineer complex information systems in terms of independent agents. These agents may collaborate in a computational organization (Multi-Agent Systems, MAS) by playing some specific roles having to interact with others in order to reach a global or individual goal. In addition, due to the complex nature of this type of systems, dealing with the classical functional and structural perspectives of software systems are not enough. The organizational perspective, that describes the context where these agents need to collaborate, and the social behavior perspective, that describes the different "intelligent" manners in which these agents can collaborate, need to be identified and properly specified. Several methodologies have been proposed to drive the development of MAS (e.g., Ingenias, Gaia, Tropos) although most of them mainly focus on the design and implementation phases and do not provide adequate mechanisms for capturing, defining, and specifying software requirements. Poor requirements engineering is recognized as the root of most errors in current software development projects, and as a means for improving the quality of current practices in the development of MAS, the main objective of this work is to propose a requirements modeling process to deal with software requirements covering the functional, structural, organizational, and social behavior perspectives of MAS. The requirements modeling proposed is developed within the model-driven engineering context defining the corresponding metamodel and its graphical syntax. In addition, a MAS requirements modeling process is specified using the Object Management Group's (OMG) Software Process Engineering Metamodel (SPEM). Finally, in order to illustrate the feasibility of our approach, we specified the software requirements of a strategic board game (the Diplomacy game).Rodríguez Viruel, ML. (2011). Requirements Modeling for Multi-Agent Systems. http://hdl.handle.net/10251/11416Archivo delegad