A robust agent design for dynamic SCM environments

ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS(2006)

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摘要
The leap from decision support to autonomous systems has often raised a number of issues, namely system safety, soundness and security. Depending on the field of application, these issues can either be easily overcome or even hinder progress. In the case of Supply Chain Management (SCM), where system performance implies loss or profit, these issues are of high importance. SCM environments are often dynamic markets providing incomplete information, therefore demanding intelligent solutions which can adhere to environment rules, perceive variations, and act in order to achieve maximum revenue. Advancing on the way such autonomous solutions deal with the SCM process, we have built a robust, highly-adaptable and easily-configurable mechanism for efficiently dealing with all SCM facets, from material procurement and inventory management to goods production and shipment. Our agent has been crash-tested in one of the most challenging SCM environments, the trading agent competition SCM game and has proven capable of providing advanced SCM solutions on behalf of its owner. This paper introduces Mertacor and its main architectural primitives, provides an overview of the TAC SCM environment, and discusses Mertacor's performance.
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关键词
autonomous system,scm process,discusses mertacor,scm environment,scm facet,dynamic scm environment,advanced scm solution,autonomous solutions deal,challenging scm environment,trading agent competition scm,robust agent design,tac scm environment,decision support,supply chain management,system safety,system performance,incomplete information
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