Abstract. It is well accepted that different types of distributed architectures require different degrees of coupling. For example, in client-server and three-tier architectures, application components are generally tightly coupled, both with one-another and with the underlying middleware. Meanwhile, in off-line transaction processing, grid computing and mobile applications, the degree of coupling between application components and with the underlying middleware needs to be minimised. Terms such as "synchronous", "asynchronous", "blocking", "non-blocking", "directed", and "non-directed" are often used to refer to the degree of coupling required by an architecture or provided by a middleware. However, these terms are used with various connotations. And while various informal definitions have been provided, there is a lack of an overarching formal framework to unambiguously communicate architectural requirements with respect to (de-)coupling. This article addresses this gap by: (i) formally defining three dimensions of (de-)coupling; (ii) relating these dimensions to existing middleware; and (iii) proposing notational elements to represent various coupling integration patterns. This article also discusses a prototype that demonstrates the feasibility of its implementation.
This paper presents an approach to develop bidding agents that participate in multiple alternative auctions, with the goal of obtaining an item with a given probability. The approach consists of a prediction method and a planning algorithm. The prediction method exploits the history of past auctions in order to build probability functions capturing the belief that a bid of a given price may win a given auction. The planning algorithm computes a price, such that by sequentially bidding in a subset of the relevant auctions, the agent can obtain the item at that price with the desired probability. The approach addresses the case where the auctions are for substitutive items with different values. Experimental results show that the approach increases the payoff of their users and the welfare of the market.
This paper presents an approach to develop bidding agents that participate in multiple alternative auctions, with the goal of obtaining an item at the lowest price. The approach consists of a prediction method and a planning algorithm. The prediction method exploits the history of past auctions in order to build probability functions capturing the belief that a bid of a given price may win a given auction. The planning algorithm computes the lowest price, such that by sequentially bidding in a subset of the relevant auctions, the agent can obtain the item at that price with an acceptable probability. The approach addresses the case where the auctions are for substitutable items with different values. Experimental results are reported, showing that the approach increases the payoff of their users and the welfare of the market.
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