Browsing by Author "Ketter, Wolfgang"

Now showing 1 - 6 of 6
  • Thumbnail Image
    Item
    Design and Analysis of the MinneTAC-03 Supply-Chain Trading Agent
    (2004-04-26) Ketter, Wolfgang; Kryzhnyaya, Elena; Damer, Steven; McMillen, Colin; Agovic, Amrudin; Collins, John; Gini, Maria
    MinneTAC is an agent designed to compete in the Supply-Chain Trading Agent Competition. It is also designed to support the needs of a group of researchers, each of whom is interested in different decision problems related to the competition scenario. The design of MinneTAC breaks outeach basic behavior into a separate, configurable component. Dependencies between components are almost non-existent. This design allows each user to focus on a single problem and work independently, and it allows multiple user to tackle the same problem in different ways. This paper describes the design of MinneTAC and evaluates its effectiveness in support of our research agenda, and in its competitiveness in the TAC-SCM game environment. We also describe two sales strategies used by MinneTAC. Both strategies estimate, as the game progresses, the probability of receiving a customer order for different prices and compute the expected profit. Offers are made to maximize the expected profit on each order. The maindifference between the two strategies is in how the probability of receiving an order and the offer prices are computed. The first strategy works well in high-demand games, the second was developed to improve performance in low-demand games. We empirically analyze the effect of the discount given by suppliers on orders received the firstday of the game, and we show that in high-demand games there is a strong correlation between the offers an agent receives from suppliers on the first day of the game and the agent's performance in the game.
  • Thumbnail Image
    Item
    Detecting and Forecasting Economic Regimes in Automated Exchanges
    (2007-03-05) Ketter, Wolfgang; Collins, John; Gini, Maria; Gupta, Alok; Schrater, Paul
    We present basic building blocks of an agent that can use observable market conditions to characterize the microeconomic conditions of the market and predict future market trends. The agent can use this information to make both tactical decisions such as pricing and strategic decisions such as product mix and production planning. We develop methods that can learn dominant market conditions, such as over-supply or scarcity, from historical data using computational methods to construct price density functions. We discuss how this knowledge can be used, together with real-time observable information, to identify the current dominant market condition and to forecast market changes over a planning horizon. We validate our methods by presenting experimental results in a case study, the Trading Agent Competition for Supply Chain Management.
  • Thumbnail Image
    Item
    Flexible decision support in dynamic interorganizational networks
    (2009-11-23) Collins, John; Ketter, Wolfgang; Gini, Maria
    An effective Decision Support System (DSS) should help its users improve decision-making in complex, information-rich, dynamic environments. We present a feature gap analysis of current decision support technologies, and we identify a set of DSS Desiderata, properties that can contribute both effectiveness and flexibility to users in such environments. We show that there is a gap between the features provided by current DSS technologies and the DSS Desiderata we aim for. We present a design-science approach that extends the boundaries of human decision-makers by creating a new and innovative artifact called "evaluator service networks" at the confluence of people, organizations, and technology. Our artifact enables users to compose decision behaviors from separate, configurable components, and allows dynamic construction of analysis and modeling tools from small, single-purpose evaluator services. The result is a network that can easily be configured to test hypotheses and analyze the impact of various choices for elements of decision processes. We have implemented and tested this design in an interactive version of the MinneTAC trading agent, an agent designed for the Trading Agent Competition for Supply Chain Management. We present an example of an evaluator service network that determines sales prices in a rich, dynamic trading environment. Additionally we describe visual interface elements that allow users to see and manipulate the configuration of the network, and to construct economic dashboards that can display the current and historical state of any node in the network.
  • Thumbnail Image
    Item
    Flexible decision support in dynamic interorganizational networks
    (2008-11-10) Collins, John; Ketter, Wolfgang; Gini, Maria
    This Technical Report has been completely re-written and re-released as #09-028. The updated version is available for download at its new location: http://www.cs.umn.edu/research/technical_reports.php?page=report&report_id=09-028
  • Thumbnail Image
    Item
    Software architecture of the MinneTAC supply-chain trading agent
    (2008-10-20) Collins, John; Ketter, Wolfgang; Gini, Maria; Agovic, Amrudin
    The MinneTAC trading agent is designed to compete in the Supply-Chain Trading Agent Competition. It is also designed to support the needs of a group of researchers, each of whom is interested in different decision problems related to the competition scenario. The design of MinneTAC breaks out each basic behavior into a separate, configurable component, and allows dynamic construction of analysis and modeling tools from small, single-purpose "evaluators". The agent is defined as a set of "roles", and a working agent is one for which a component is supplied for each role. This allows each researcher to focus on a single problem and work independently, and it allows multiple researchers to tackle the same problem in different ways. A working MinneTAC agent is completely defined by a set of configuration files that map the desired roles to the code that implements them, and that set parameters for the components. We describe the design of MinneTAC, and we evaluate its effectiveness in support of our research agenda and its competitiveness in the TAC-SCM game environment.
  • Thumbnail Image
    Item
    Tactical and Strategic Sales Management for Intelligent Agents Guided By Economic Regimes
    (2008-10-20) Ketter, Wolfgang; Collins, John; Gini, Maria; Gupta, Alok; Schrater, Paul
    We present a computational approach that autonomous software agents can adopt to make tactical decisions, such as product pricing, and strategic decisions, such as product mix and production planning, to maximize profit in markets with supply and demand uncertainties. Using a combination of machine learning and optimization techniques, the agent is able to characterize economic regimes, which are historical microeconomic conditions reflecting situations such as over-supply and scarcity. We assume an agent is capable of using real-time observable information to identify the current dominant market condition and we show how it can forecast regime changes over a planning horizon. We demonstrate how the agent can then use regime characterization to predict prices, price trends, and the probability of receiving a customer order in a dynamic supply chain environment. We validate our methods by presenting experimental results from a testbed derived from the Trading Agent Competition for Supply Chain Management (TAC SCM). The results show that our agent outperforms traditional short- and long-term predictive methodologies (such as exponential smoothing) significantly, resulting in accurate prediction of customer order probabilities, and competitive market prices. This, in turn, has the potential to produce higher profits. We also demonstrate the versatility of our computational approach by applying the methodology to prediction of stock price trends.