John Collins

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We present a system for multi-agent contract negotiation, implemented as a generalized market architecture called MAGNET. MAGNET provides support for a variety of types of transactions, from simple buying and selling of goods and services to complex multi-agent contract negotiations. In the latter case, MAGNET is designed to negotiate contracts based on(More)
WC present a testbed for multi-agent negotiation, implemcntcd as a gcncralizcd market architecture called MAGNET (Multi AGcnt NEgotiation Testbed). In contrast with other approaches to multi-agent negotiation, we introduce an explicit intermediary into the negotiation process. We show how this approach helps in controlling fraud and discouraging(More)
We are interested in supporting multi-agent contracting, in which customer agents solicit the resources and capabilities of other, self-interested agents in order to accomplish their goals. Goals may involve the execution of multi-step tasks, in which different tasks are contracted out to different suppliers. We have developed a testbed that allows us to(More)
The Magnet system meets many of the challenges of modeling decision making for customer agents in automated contract negotiation. B usiness-to-business e-commerce is expanding rapidly, letting manufacturers both broaden their customer base and increase their pool of potential suppliers. However, negotiating supplier contracts for the multiple components(More)
We describe two sales strategies used by our agent, MinneTAC, for the 2003 Supply Chain Management Trading Agent Competition (TAC SCM). Both strategies estimate, as the game progresses, the probability of receiving a customer order for different prices and compute the expected profit. We empirically analyze the effect of the discount given by suppliers on(More)
We extend the IP models proposed by Nisan and Andersson for winner determination in combinatorial auctions, to the problem of evaluating bids for coordinated task sets. This requires relaxing the free disposal assumption, and encoding temporal constraints in the model. We present a basic model, along with an improved model that dramatically reduces the(More)
We present methods for an autonomous agent to identify dominant market conditions, such as over-supply or scarcity, and to predict market changes. The characteristics of economic regimes are learned from historic data and used, together with real-time observable information, to identify the current market regime and to forecast market changes. We use a(More)
We extend Sandholm’s bidtree-based IDA* algorithm for combinatorial auction winner determination to deal with negotiation over tasks with precedence constraints. We evaluate its performance, and show that the order of items in the bidtree has a major impact on performance. Specifically, performance is enhanced if the items with the largest numbers of bids(More)
Modern electronic commerce creates significant challenges for decision-makers. The trading agent competition for supply-chain management (TAC SCM) is an annual competition among fully-autonomous trading agents designed by teams around the world. Agents attempt to maximize profits in a supplychain scenario that requires them to coordinate Procurement,(More)