The significance of bidding, accepting and opponent modeling in automated negotiation

Given the growing interest in automated negotiation, the search for effective strategies has produced a variety of different negotiation agents. Despite their diversity, there is a common structure to their design. A negotiation agent comprises three key components: the bidding strategy, the opponent model and the acceptance criteria. We show that this three-component view of a negotiating architecture not only provides a useful basis for developing such agents but also provides a useful analytical tool. By combining these components in varying ways, we are able to demonstrate the contribution of each component to the overall negotiation result, and thus determine the key contributing components. Moreover, we are able to study the interaction between components and present detailed interaction effects. Furthermore, we find that the bidding strategy in particular is of critical importance to the negotiator's success and far exceeds the importance of opponent preference modeling techniques. Our results contribute to the shaping of a research agenda for negotiating agent design by providing guidelines on how agent developers can spend their time most effectively

An Evolutionary Learning Approach for Adaptive Negotiation Agents

Developing effective and efficient negotiation mechanisms for real-world applications such as e-Business is challenging since negotiations in such a context are characterised by combinatorially complex negotiation spaces, tough deadlines, very limited information about the opponents, and volatile negotiator preferences. Accordingly, practical negotiation systems should be empowered by effective learning mechanisms to acquire dynamic domain knowledge from the possibly changing negotiation contexts. This paper illustrates our adaptive negotiation agents which are underpinned by robust evolutionary learning mechanisms to deal with complex and dynamic negotiation contexts. Our experimental results show that GA-based adaptive negotiation agents outperform a theoretically optimal negotiation mechanism which guarantees Pareto optimal. Our research work opens the door to the development of practical negotiation systems for real-world applications

Acceptance conditions in automated negotiation

In every negotiation with a deadline, one of the negotiating parties has to accept an offer to avoid a break off. A break off is usually an undesirable outcome for both parties, therefore it is important that a negotiator employs a proficient mechanism to decide under which conditions to accept. When designing such conditions one is faced with the acceptance dilemma: accepting the current offer may be suboptimal, as better offers may still be presented. On the other hand, accepting too late may prevent an agreement from being reached, resulting in a break off with no gain for either party. Motivated by the challenges of bilateral negotiations between automated agents and by the results and insights of the automated negotiating agents competition (ANAC), we classify and compare state-of-the-art generic acceptance conditions. We focus on decoupled acceptance conditions, i.e. conditions that do not depend on the bidding strategy that is used. We performed extensive experiments to compare the performance of acceptance conditions in combination with a broad range of bidding strategies and negotiation domains. Furthermore we propose new acceptance conditions and we demonstrate that they outperform the other conditions that we study. In particular, it is shown that they outperform the standard acceptance condition of comparing the current offer with the offer the agent is ready to send out. We also provide insight in to why some conditions work better than others and investigate correlations between the properties of the negotiation environment and the efficacy of acceptance condition

Anonymous network access using the digital marketplace

With increasing usage of mobile telephony, and the trend towards additional mobile Internet usage, privacy and anonymity become more and more important. Previously-published anonymous communication schemes aim to obscure their users' network addresses, because real-world identity can be easily be derived from this information. We propose modifications to a novel call-management architecture, the digital marketplace, which will break this link, therefore enabling truly anonymous network access

An argumentation system that builds trusted trading partnerships

University of Technology, Sydney. Faculty of Engineering and Information Technology.In e-Commerce, a buying process typically begins with browsing the available products or services, and then selecting the ones that satisfy a given need. The next phase is negotiation to reach an agreement. If an agreement is signed between two parties, they enter into the enactment phase including payment and delivery. After that, they evaluate how well the products or services satisfy their needs. One of the reasons for dissatisfaction is that a trading agent does not know its opponent agent's needs, contract acceptance criteria, or behaviour during their interactions. This dissertation is concerned with the problems and challenges of repeatedly conducted trading activities in e-Commerce applications. Argumentation is a mode of interaction between agents that enables them to exchange information within messages in the form of arguments to explain their current position and future plans with the intention of increasing the chance of success in the negotiation. How an agent conducts all phases of a buying process through argumentation is an important research query. It becomes difficult to solve this query if an agent has to repeatedly conduct trading activities with its opponent agents. This work describes a novel solution to how an agent builds trusted trading partnerships with its opponent agents. The requirements of all phases of a buying process are specified by five models: the needs model, the opponent agent selection model, the communication model, the agreement model, and the relationship model. The relationship aware argumentation framework is then proposed. It integrates how the trading agents analyze their interaction history, exchanged information, and any promises made. An agent architecture is then developed that extends the idea of information based agency. It measures the strength of business relationships and predicts behavioural parameters from the history of interactions. This dissertation establishes the thesis statement, "Modelling the strength of relationships between agents and predicting the behaviour of trading partner agents in a multi agent argumentation system enables agents to build trusted trading partnerships". A prototype simulation environment has been developed to conduct the experiments and to validate the thesis statement. The simulated arrival rate obtained by the proposed model is lower than that of an existing model, e.g., the Trust and Honour model. The prototype argumentation system demonstrated a proof of concept. The prototype will be further developed before applying the proposed argumentation system in commercial applications

Cooperative-Competitive Healthcare Service Negotiation

Service negotiation is a complex activity, especially in complex domains such as healthcare. The provision of healthcare services typically involves the coordination of several professionals with different skills and locations. There is usually negotiation between health- care service providers as different services have specific constraints, variables, and features (scheduling, waiting lists, availability of resources, etc.), which may conflict with each other. While automating the negotiation processes by using software can improve the e±ciency and quality of healthcare services, most of the existing negotiation automations are positional bargaining in nature, and are not suitable for complex scenarios in healthcare services. This paper proposes a cooperative-competitive negotiation model that enables negotiating parties to share their knowledge and work toward optimal solutions. In this model, patients and healthcare providers work together to develop a patient-centered treatment plan. We further automate the new negotiation model with software agents

On integrating Theory of Mind in context-aware negotiation agents

Theory of Mind (ToM) is the ability of an agent to represent mental states of other agents including their intentions, desires, goals, models, beliefs, how the environment makes an impact on those beliefs, and the beliefs those agents may have about the beliefs others have about themselves. Integrating arti cial ToM in automated negotiations can provide software agents a key competitive advantage. In this work, we propose integrating ToM into context-aware negotiation agents using Bayesian inference to update each agent's beliefs. Beliefs are about the necessity and risk of the opponent considering hypothesis about how it takes into account contextual variables. A systematic hierarchical approach to combine ToM with using evidence from the opponent actions in an unfolding negotiation episode is proposed. Alternative contextual scenarios are used to argue in favor of incorporating di erent levels of reasoning and modeling the strategic behavior of an opponent.Sociedad Argentina de Informática e Investigación Operativ

On integrating Theory of Mind in context-aware negotiation agents

Theory of Mind (ToM) is the ability of an agent to represent mental states of other agents including their intentions, desires, goals, models, beliefs, how the environment makes an impact on those beliefs, and the beliefs those agents may have about the beliefs others have about themselves. Integrating arti cial ToM in automated negotiations can provide software agents a key competitive advantage. In this work, we propose integrating ToM into context-aware negotiation agents using Bayesian inference to update each agent's beliefs. Beliefs are about the necessity and risk of the opponent considering hypothesis about how it takes into account contextual variables. A systematic hierarchical approach to combine ToM with using evidence from the opponent actions in an unfolding negotiation episode is proposed. Alternative contextual scenarios are used to argue in favor of incorporating di erent levels of reasoning and modeling the strategic behavior of an opponent.Sociedad Argentina de Informática e Investigación Operativ