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

Automated Purchase Negotiations in a Dynamic Electronic Marketplace

Nowadays, there is a surge of B2C and B2B e-commerce operated\ud on the Internet. However, many of these systems are often nothing\ud more than electronic product or service catalogues. Against this background,\ud it is argued that new generation systems based on automatic\ud negotiation will emerge. This paper covers a particular kind of automatic\ud negotiation systems, where a number of participants in a mobile\ud dynamic electronic marketplace automatically negotiate the purchase of\ud products or services, by means of multiple automated one-to-one bargainings.\ud In a dynamic e-marketplace, the number of buyers and sellers\ud and their preferences may change over time. By mobile we mean that\ud buyers in a commercial area may initiate simultaneous negotiations with\ud several sellers using portable devices like cell phones, laptops or personal\ud digital assistants, so these negotiations do not require participants to be\ud colocated in space. We will show how an expressive approach to fuzzy\ud constraint based agent purchase negotiations in competitive trading environments,\ud is ideally suited to work on these kind of e-marketplaces. An\ud example of mobile e-marketplace, and a comparison between an expressive\ud and an inexpressive approach will be presented to show the efficiency\ud of the proposed solution

Spatio-Temporal Context in Agent-Based Meeting Scheduling

Meeting scheduling is a common task for organizations of all sizes. It involves searching for a time and place when and where all the participants can meet. However, scheduling a meeting is generally difficult in that it attempts to satisfy the preferences of all participants. Negotiation tends to be an iterative and time consuming task. Proxy agents can handle the negotiation on behalf of the individuals without sacrificing their privacy or overlooking their preferences. This thesis examines the implications of formalizing meeting scheduling as a spatiotemporal negotiation problem. The “Children in the Rectangular Forest” (CRF) canonical model is applied to meeting scheduling. By formalizing meeting scheduling within the CRF model, a generalized problem emerges that establishes a clear relationship with other spatiotemporal distributed scheduling problems. The thesis also examines the implications of the proposed formalization to meeting scheduling negotiations. A protocol for meeting location selection is presented and evaluated using simulations

Coordinated constraint relaxation using a distributed agent protocol

The interactions among agents in a multi-agent system for coordinating a distributed, problem solving task can be complex, as the distinct sub-problems of the individual agents are interdependent. A distributed protocol provides the necessary framework for specifying these interactions. In a model of interactions where the agents' social norms are expressed as the message passing behaviours associated with roles, the dependencies among agents can be specified as constraints. The constraints are associated with roles to be adopted by agents as dictated by the protocol. These constraints are commonly handled using a conventional constraint solving system that only allows two satisfactory states to be achieved - completely satisfied or failed. Agent interactions then become brittle as the occurrence of an over-constrained state can cause the interaction between agents to break prematurely, even though the interacting agents could, in principle, reach an agreement. Assuming that the agents are capable of relaxing their individual constraints to reach a common goal, the main issue addressed by this thesis is how the agents could communicate and coordinate the constraint relaxation process. The interaction mechanism for this is obtained by reinterpreting a technique borrowed from the constraint satisfaction field, deployed and computed at the protocol level.The foundations of this work are the Lightweight Coordination Calculus (LCC) and the distributed partial Constraint Satisfaction Problem (CSP). LCC is a distributed interaction protocol language, based on process calculus, for specifying and executing agents' social norms in a multi-agent system. Distributed partial CSP is an extension of partial CSP, a means for managing the relaxation of distributed, over-constrained, CSPs. The research presented in this thesis concerns how distributed partial CSP technique, used to address over-constrained problems in the constraint satisfaction field, could be adopted and integrated within the LCC to obtain a more flexible means for constraint handling during agent interactions. The approach is evaluated against a set of overconstrained Multi-agent Agreement Problems (MAPs) with different levels of hardness. Not only does this thesis explore a flexible and novel approach for handling constraints during the interactions of heterogeneous and autonomous agents participating in a problem solving task, but it is also grounded in a practical implementation

A hybrid model of electronic negotiation : integration of negotiation support and automated negotiation models

Electronic business negotiations are enabled by different electronic negotiation models: automated negotiation models for software agents, negotiation support models for human negotiators, and auction models for both. To date, there is no electronic negotiation model that enables bilateral multi-issue negotiations between a human negotiator and a negotiation agent?an important task in electronic negotiation research. In this thesis, a model is presented that integrates the automated negotiation model and the negotiation support model. The resulting hybrid negotiation model paves the way for human-agent business negotiations. The integration of two models is realised at the levels of negotiation process, communication support and decision making. To this end, the negotiation design, negotiation process, negotiation decision making, and negotiation communication in negotiation support systems (NSSs) and agent negotiation systems (ANSs) are studied and analysed. The analyses on these points help in strengthening the motivation behind hybrid negotiation model and setting aims for the integration of an NSS and an ANS in hybrid negotiation model. We mainly propose a human-agent negotiation design, negotiation process protocols to support the design, a hybrid communication model for human-agent interaction, an agent decision-making model for negotiation with human, and a component for interoperability between NSS and ANS. The agent decision-making model is composed of heuristic and argumentation-based negotiation techniques. It is proposed after analysing different automated negotiation models for different human negotiation strategies. The proposed communication model supports human negotiator and negotiation agent to understand and process negotiation messages from each other. This communication model consists of negotiation ontology, a wrapper agent, and a proper selection of an agent communication language (ACL) and a content language. The wrapper agent plays a role for interoperability between agent system and NSS by providing a communication interface along with the negotiation ontology. The negotiation ontology, ACL and agent content language make the communication model of negotiation agent in ANS. The proposed hybrid model is realised by integrating an ANS into NSS Negoisst. The research aim is to show that a hybrid negotiation system, composed of two heterogeneous negotiation models, can enable human-agent multi-issue integrative negotiations.Elektronische ökonomische Verhandlungen werden durch verschiedene Verhandlungsmodelle ermöglicht: Automatisierte Verhandlungsmodelle für Softwareagenten, Verhandlungsunterstützung für menschliche Verhandelnde und Auktionsmodelle für Beide. Bis heute existiert kein elektronisches Verhandlungsmodell, das bilaterale multi-attributive Verhandlungen zwischen einem menschlichen Verhandelnden und einem Verhandlungsagenten ? eine wichtige Aufgabe in der Forschung im Bereich elektronischer Verhandlungen. In dieser Arbeit wird ein Modell präsentiert, welches das automatisierte Verhandlungsmodell und das Verhandlungsunterstützungsmodell integriert. Das resultierende hybride Verhandlungsmodell ebnet den Weg für ökonomische Mensch-Agent-Verhandlungen. Die Integration der zwei Modelle ist realisiert auf der Ebene von Verhandlungsprozess, Kommunikationsunterstützung und Entscheidungsunterstützung. Dazu werden Verhandlungsdesign, Verhandlungsprozess, verhandlungsbezogene Entscheidungsfindung und Verhandlungskommunikation in Verhandlungsunterstützungssystemen (NSS) und Agentenverhandlungssystemen (ANS) studiert und analysiert. Die Analysen zu diesen Punkten verstärken die Motivation hinter dem hybriden Verhandlungsmodell und bestimmen die Ziele für die Integration von NSS und ANS. Es werden hauptsächlich ein Mensch-Agent-Verhandlungsdesign, Verhandlungsprozessprotokolle zur Unterstützung des Designs, ein hybrides Kommunikationsmodell für Mensch-Agent-Kommunikation, ein Agenten-Entscheidungsmodell für die Verhandlung mit menschlichem Gegenpart und eine Komponente für die Interoperabilität zwischen NSS und ANS. Das Entscheidungsmodell für Agenten besteht aus heuristischen und argumentativen Verhandlungstechniken. Es wird aufgestellt nachdem verschiedene automatisierte Verhandlungsmodelle für verschiedene menschliche Verhandlungsstrategien analysiert worden sind. Die vorgeschlagenen Kommunikationsmodelle unterstützen menschliche Verhandler und Verhandlungsagenten dabei Verhandlungsnachrichten voneinander zu verstehen und zu verarbeiten. Dieses Kommunikationsmodell besteht aus einer Verhandlungsontologie, einem Wrapper-Agenten und einer angemessenen Auswahl der Agentenkommunikationssprache (ACL) und der Inhaltssprache. Der Wrapper-Agent spielt eine Rolle bei der Interoperabilität zwischen dem Agentensystem und dem NSS durch eine Kommunikationsschnittstelle zusammen mit der Verhandlungsontologie. Die Verhandlungsontologie, die ACL und die Inhaltssprache der Agenten ergeben das Kommunikationsmodell der Verhandlungsagenten im ANS. Das vorgestellte hybride Modell ist realisiert als Integration eines ANS in das NSS Negoisst. Das Forschungsziel ist zu zeigen, dass ein hybrides Verhandlungssystem, basierend auf zwei heterogenen Verhandlungsmodellen, integrative multi-attributive Mensch-Agent-Verhandlungen ermöglicht

Improving problem definition through interactive evolutionary computation

Poor definition and uncertainty are primary characteristics of conceptual design processes. During the initial stages of these generally human-centric activities, little knowledge pertaining to the problem at hand may be available. The degree of problem definition will depend on information available in terms of appropriate variables, constraints, and both quantitative and qualitative objectives. Typically, the problem space develops with information gained in a dynamical process in which design optimization plays a secondary role, following the establishment of a sufficiently well-defined problem domain. This paper concentrates on background human-computer interaction relating to the machine-based generation of high-quality design information that, when presented in an appropriate manner to the designer, supports a better understanding of a problem domain. Knowledge gained from such information combined with the experiential knowledge of the designer can result in a reformulation of the problem, providing increased definition and greater confidence in the machine-based representation. Conceptual design domains related to gas turbine blade cooling systems and a preliminary air frame configuration are introduced. These are utilized to illustrate the integration of interactive evolutionary strategies that support the extraction of optimal design information, its presentation to the designer, and subsequent human-based modification of the design domain based on knowledge gained from the information received. An experimental iterative designer or evolutionary search process resulting in a better understanding of the problem and improved machine-based representation of the design domain is thus established

Proceedings of the third International Workshop of the IFIP WG5.7

Contents of the papers presented at the international workshop deal with the wide variety of new and computer-based techniques for production planning and control that has become available to the scientific and industrial world in the past few years: formal modeling techniques, artificial neural networks, autonomous agent theory, genetic algorithms, chaos theory, fuzzy logic, simulated annealing, tabu search, simulation and so on. The approach, while being scientifically rigorous, is focused on the applicability to industrial environment

Coordination mechanisms with mathematical programming models for decentralized decision-making, a literature review

[EN] The increase in the complexity of supply chains requires greater efforts to align the activities of all its members in order to improve the creation of value of their products or services offered to customers. In general, the information is asymmetric; each member has its own objective and limitations that may be in conflict with other members. Operations managements face the challenge of coordinating activities in such a way that the supply chain as a whole remains competitive, while each member improves by cooperating. This document aims to offer a systematic review of the collaborative planning in the last decade on the mechanisms of coordination in mathematical programming models that allow us to position existing concepts and identify areas where more research is needed.Rius-Sorolla, G.; Maheut, J.; Estelles Miguel, S.; García Sabater, JP. (2020). Coordination mechanisms with mathematical programming models for decentralized decision-making, a literature review. 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