Larks: Dynamic Matchmaking Among Heterogeneous Software Agents in Cyberspace

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In this paper we define the notions of agent matchmaking and brokering behaviors that are used while processing requests among initially unacquainted sets of agents. These behaviors are basic components of common organizational roles and thus must be understood by computational agents. Brokering and matchmaking behaviors can be used to construct organizational forms such as centralized or distributed markets, ad hoc teams, and bureaucratic functional or product hierarchies.

Each behavior brings with it certain performance characteristics — cost, robustness, and adaptiveness qualities — that are related to characteristics of the external environment and of the agents themselves. For example, while brokered systems are more vulnerable to certain failures, they are also able to cope more quickly with a rapidly fluctuating agent workforce.

We present several agent design constraints and related models, which are experimentally validated using the WARREN multi-agent portfolio management system. Matchmaking and Brokering Katia Sycara , K. Decker and M.

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By Bart Taylor Apr 12, As gratifying it is to watch the country rally around manufacturing, new laws that would incent companies to reshore jobs, or require companies to source domestically, will run headlong into issues that force companies offshore in the first place, including the most obvious: an inability to find qualified, cost-effective suppliers in the U. It’s why the sector’s next great challenge is to connect America’s importers — its product brands and manufacturers — with domestic suppliers that map to their needs, one by one, company by company.

It’s not a new idea. Literally every trade or industry group has expended money or energy on supply-chain mapping. We continue to try, and fall short. Harry Moser is founder of the Reshoring Initiative RI and has studied the economics of offshore production for more than a decade. Moser has quantified reshoring activity throughout the past decade. In , it fell off to about ,, and our preliminary numbers for say about , jobs, off a third from but still 20 times greater than ,” Moser explains.

Why the falloff later in the decade? Call it a hangover from the certainty of tax and regulatory cuts to the chaos of a trade war. Still, he sees a quick recovery under certain conditions. What types of companies will reshore in the future? Easy reply.

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Service matchmaking among heterogeneous software agents in the Internet is usually done dynamically and must be efficient. There is an obvious trade-off between the quality and efficiency of matchmaking on the Internet. We define a language called Larks for agent advertisements and requests, and present a flexible and efficient matchmaking process that uses Larks. The Larks matchmaking process performs both syntactic and semantic matching, and in addition allows the specification of concepts local ontologies via ITL, a concept language.

The matching process uses five different filters: context matching, profile comparison, similarity matching, signature matching and constraint matching. Different degrees of partial matching can result from utilizing different combinations of these filters. We briefly report on our implementation of Larks and the matchmaking process in Java. Fielded applications of matchmaking using Larks in several application domains for systems of information agents are ongoing efforts.

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Why supply-chain matchmaking is a crucial next step, and how to accomplish it

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