Towards a quantitative concession-based classification method of negotiation strategies

In order to successfully reach an agreement in a negotiation, both parties rely on each other to make concessions. The willingness to concede also depends in large part on the opponent. A concession by the opponent may be reciprocated, but the negotiation process may also be frustrated if the opponent does not concede at all.This process of concession making is a central theme in many of the classic and current automated negotiation strategies. In this paper, we present a quantitative classification method of negotiation strategies that measures the willingness of an agent to concede against different types of opponents. The method is then applied to classify some well-known negotiating strategies, including the agents of ANAC 2010. It is shown that the technique makes it easy to identify the main characteristics of negotiation agents, and can be used to group negotiation strategies into categories with common negotiation characteristics. We also observe, among other things, that different kinds of opponents call for a different approach in making concession

An Evolutionary Approach for Learning Opponent's Deadline and Reserve Points in Multi-Issue Negotiation

The efficiency of automated multi-issue negotiation depends on the available information about the opponent. In a competitive negotiation environment, agents do not reveal their parameters to their opponents in order to avoid exploitation. Several researchers have argued that an agent's optimal strategy can be determined using the opponent's deadline and reserve points. In this paper, we propose a new learning agent, so-called Evolutionary Learning Agent (ELA), able to estimate its opponent's deadline and reserve points in bilateral multi-issue negotiation based on opponent's counter-offers (without any additional extra information). ELA reduces the learning problem to a system of non-linear equations and uses an evolutionary algorithm based on the elitism aspect to solve it. Experimental study shows that our learning agent outperforms others agents by improving its outcome in term of average and joint utility

Evaluating practical negotiating agents: Results and analysis of the 2011 international competition

This paper presents an in-depth analysis and the key insights gained from the Second International Automated Negotiating Agents Competition (ANAC 2011). ANAC is an international competition that challenges researchers to develop successful automated negotiation agents for scenarios where there is no information about the strategies and preferences of the opponents. The key objectives of this competition are to advance the state-of-the-art in the area of practical bilateral multi-issue negotiations, and to encourage the design of agents that are able to operate effectively across a variety of scenarios. Eighteen teams from seven different institutes competed. This paper describes these agents, the setup of the tournament, including the negotiation scenarios used, and the results of both the qualifying and final rounds of the tournament. We then go on to analyse the different strategies and techniques employed by the participants using two methods: (i) we classify the agents with respect to their concession behaviour against a set of standard benchmark strategies and (ii) we employ empirical game theory (EGT) to investigate the robustness of the strategies. Our analysis of the competition results allows us to highlight several interesting insights for the broader automated negotiation community. In particular, we show that the most adaptive negotiation strategies, while robu

Computational intelligence based complex adaptive system-of-systems architecture evolution strategy

The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving SoS architecture based on the wave model through three key features namely; meta-architecture generation, architecture assessment and architecture implementation. Meta-architectures are generated using evolutionary algorithms and assessed using type II fuzzy nets. The approach can accommodate diverse stakeholder views and convert them to key performance parameters (KPP) and use them for architecture assessment. On the other hand, it is not possible to implement such architecture without persuading the systems to participate into the meta-architecture. To address this issue a negotiation model is proposed which helps the SoS manger to adapt his strategy based on system owners behavior. This work helps in capturing the varied differences in the resources required by systems to prepare for participation. The viewpoints of multiple stakeholders are aggregated to assess the overall mission effectiveness of the overarching objective. An SAR SoS example problem illustrates application of the method. Also a dynamic programing approach can be used for generating meta-architectures based on the wave model. --Abstract, page iii

A Framework for Argumentation-Based Agent Negotiation in Uncertain Settings

Automated negotiation technologies are being increasingly used in business applications, especially in the e-Commerce domain. Argumentation-Based Negotiation (ABN), among the existing approaches, has been distinguished as a powerful approach to automated negotiation due to its ability to provide more sophisticated information (arguments) that justifies and supports agents’ proposals in order to mutually influence their preference relations on the set of offers, and consequently on the negotiation outcome. During the recent years, argumentation-based negotiation has received a considerable attention in the area of agent communication. However, current proposals are mostly concerned with presenting protocols for showing how agents can interact with each other, and how arguments and offers can be generated, evaluated and exchanged under the assumption of certainty. Therefore, none of these proposals is directly targeting the agents’ uncertainty about the selection of their moves nor designing the appropriate negotiation strategies based on this uncertainty in order to help the negotiating agents better make their decisions in the negotiation settings where agents have limited or uncertain information, precluding them from making optimal individual decisions. In this thesis, we tackle the aforementioned problems by advocating an Argumentation-Based Agent Negotiation (ABAN) framework that is capable of handling the problem of agents’ uncertainty during the negotiation process. We begin by proposing an argumentation framework enriched with a new element called agent’s uncertainty as an important parameter in the agent theory to allow negotiating agents to decide which moves to play and reason about the selection of these moves under the assumption of uncertainty. Then, a method for agents’ uncertainty assessment is presented. In particular, we use Shannon entropy to assess agent’s uncertainty about their moves at each dialogue step as well as for the whole dialogue. Negotiation strategies and agent profiles issues are also explored and a methodology for designing novel negotiation strategies and agent profiles under the assumption of uncertainty is developed. Moreover, two important outcome properties namely, completeness and Nash equilibrium are discussed. Finally, the applicability of our framework is explored through several scenarios of the well-known Buyer/Seller case study. The obtained empirical results confirm the effectiveness of using our uncertainty-aware techniques and demonstrate the usefulness of using such techniques in argumentation-based negotiations

Internal Supply Chain Management - Entwicklung und experimentelle Analyse hybrider Losgrößenplanungsverfahren

Die Planungsliteratur des vergangenen Jahrzehnts ist dominiert von der Idee des Supply Chain Management. Die Supply-Chain-Planungsmodelle als integraler Bestandteil des Supply Chain Management werde in zentrale und dezentrale Modelle unterteilt. Unbestritten ist, dass unternehmensübergreifende Netzwerke von heterarchischen Organisationselementen geprägt sind. In unternehmensinternen Supply Chains, sogenannten Internal Supply Chains, sind eher hierarchische Elemente zu finden. Diese Tatsache verleitet zu der Kombination aus zentralen Planungmodellen und Internal Supply Chains. Bei genauerer Betrachtung ist aber festzustellen, dass in zahlreichen Unternehmen durchaus auch heterarchische Organisationelemente, zum Beispiel in Form von internen Märkten oder Verhandlungen, zu finden sind. Die Existenz derartiger, hybrider Strukturen in Unternehmen und damit einem Zusammenspiel aus Zentralstelle und dezentralen Einheiten wird in zahlreichen empirischen, praxisorientierten oder theoretischen Publikation beschrieben. Auf die Entwicklung hybrider Modelle, die diese Organisationsstruktur explizit berücksichtigen, wurde bislang jedoch verzichtet. Hier setzt diese Dissertation an. Im modellorientierten Teil der Arbeit werden am Beispiel der standortübergreifenden Losgrößenplanung Möglichkeiten zur Umsetzung der Organisationsstruktur aufgezeigt. Der experimentelle Teil der Arbeit enthält eine Analyse der entwickelten hybriden Modelle vor dem Hintergrund eines realistischen Entscheiderverhaltens. Hervorzuheben ist dabei die Beschreibung eines Laborexperiments, in dem Verhandlungsprozesse und -ergebnisse analysiert werden. Die zum Teil überraschenden Resultate besitzen weit über den Bereich der Losgrößenplanung hinaus Gültigkeit. Dass die Erkenntnisse dieser Arbeit generell über den Bereich der Losgrößenplanung hinausreichen, dafür sorgen die zahlreichen, skizzierten Ansätze und die allgemeinen experimentellen Erkenntnisse zum gesamten Internal Supply CHain Management und zur Zusammenarbeit zwischen zentralen Stellen und dezentralen Einheiten