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 multi-agent platform for auction-based allocation of loads in transportation logistics

This paper describes an agent-based platform for the allocation of loads in distributed transportation logistics, developed as a collaboration between CWI, Dutch National Center for Mathematics and Computer Science, Amsterdam and Vos Logistics Organizing, Nijmegen, The Netherlands. The platform follows a real business scenario proposed by Vos, and it involves a set of agents bidding for transportation loads to be distributed from a central depot in the Netherlands to different locations across Germany. The platform supports both human agents (i.e. transportation planners), who can bid through specialized planning and bidding interfaces, as well as automated, software agents. We exemplify how the proposed platform can be used to test both the bidding behaviour of human logistics planners, as well as the performance of automated auction bidding strategies, developed for such settings. The paper first introduces the business problem setting and then describes the architecture and main characteristics of our auction platform. We conclude with a preliminary discussion of our experience from a human bidding experiment, involving Vos planners competing for orders both against each other and against some (simple) automated strategies

U.S. Textile Manufacturing and the Trans-Pacific Partnership Negotiations

[Excerpt] The Trans-Pacific Partnership Agreement (TPP) is a proposed regional free trade agreement (FTA) currently under negotiation among 12 Pacific Rim countries. Initiated under President George W. Bush, the TPP concept has wide bipartisan support. As the negotiations progress, provisions concerning textile trade have become a major point of contention, attracting considerable congressional attention and debate. This report examines the potential implications of a TPP agreement, if one is reached, for the U.S. textile manufacturing industry

Rational bidding using reinforcement learning: an application in automated resource allocation

The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic resource provisioning and usage of computational resources, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a framework for supporting consumers and providers in technical and economic preference elicitation and the generation of bids. Secondly, we introduce a consumer-side reinforcement learning bidding strategy which enables rational behavior by the generation and selection of bids. Thirdly, we evaluate and compare this bidding strategy against a truth-telling bidding strategy for two kinds of market mechanisms – one centralized and one decentralized

Automatizing Price Negotiation in Commodities Markets

This is an introductory work to trade automatization of the futures market, so far operated by human traders. We are not focusing on maximizing individual profits of any trader as done in many studies, but rather we try to build a stable electronic trading system allowing to obtain a fair price, based on supply and demand dynamics, in order to avoid speculative bubbles and crashes. In our setup, producers and consumers release regularly their forecasts of output and consumption respectively. Automated traders will use this information to negotiate price of the underlying commodity. We suggested a set of analytical criteria allowing to measure the efficiency of the automatic trading strategy in respect to market stability.Automated Traders, Optimal Strategies, Futures Market, Commodities Trading

Transaction Streams: Definition and Implications for Trust in Internet-Based Electronic Commerce.

In this paper we analyze how transactions related to the exchange of goods and services are being performed on the Internet. The adoption of electronic markets in an industry has a disintermediation potential because it can create a direct link between the producer and the consumer (without the need for the intermediation role of distributors). Electronic markets lower the search cost, allowing customers to choose among more providers (which ultimately reduces both the costs for the customer and the profits for the producer). In this paper we contend that electronic markets on the Internet have the opposite effect, resulting in our increase in the number of intermediators. We introduce transaction streams, which model how transactions are being conducted and help explain the types of new intermediators that are appearing on the Internet. We also describe mechanisms by which companies are exploring ways of extending transaction streams. To illustrate the model and validate our findings, we analyze transaction streams in the insurance industry and review associated concepts such as trust and brands.transactions; electronic markets;

Q-Strategy: A Bidding Strategy for Market-Based Allocation of Grid Services

The application of autonomous agents by the provisioning and usage of computational services is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic service provisioning and usage of Grid services, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a bidding agent framework for implementing artificial bidding agents, supporting consumers and providers in technical and economic preference elicitation as well as automated bid generation by the requesting and provisioning of Grid services. Secondly, we introduce a novel consumer-side bidding strategy, which enables a goal-oriented and strategic behavior by the generation and submission of consumer service requests and selection of provider offers. Thirdly, we evaluate and compare the Q-strategy, implemented within the presented framework, against the Truth-Telling bidding strategy in three mechanisms – a centralized CDA, a decentralized on-line machine scheduling and a FIFO-scheduling mechanisms