Decision support systems (DSS) are currently used in a wide variety of applications ranging from financial planning, human resources management, weather prediction systems and strategic planning during military operation. Complex and dynamic problem domains that are difficult to model using the components of a traditional DSS characterize modern applications. Augmenting DSS with autonomous intelligent agents enables the human user and/or machine the ability to enhance traditional DSS components with knowledge that is dynamically acquired from the real-time environment. We propose to initiate the research in this area by adopting a innovative system architecture called the Intelligent Agent Enabled Decision Support (IAEDS) proposed by the PIs, Dasgupta and Khazanchi (2002). This architecture proposes employing mobile intelligent agents to make strategic decisions for humans under critical conditions aided by an adaptive decision support system. The architecture comprises unique features such as a “learning engine” and an “intelligent applet base” in its intelligent agent layer and the traditional components of decision support such as model management, an environmental database module, and a domain-specific database module in its decision support layer. As a part of this programmatic research endeavor, we propose to demonstrate the IAEDS architecture with the design and implementation of a prototype application.
Prithviraj Dasgupta and Deepak Khazanchi
Dasgupta, P. and Khazanchi, D. (2002). "Intelligent Agent-Based Decision Support Research Program". Qualified for second round of NSF EPSCoR, Nebraska.
Dasgupta, P. and Khazanchi, D. (2003). "Adaptive Decision Support Using Mobile Intelligent Agents". NSF ITR Proposal.
Dasgupta, P. and Khazanchi, D. (2002)."Adaptive Decision Support for Dynammic Situations Using Mobile Intelligent Agents". Submitted to CACM for review, 9/2002.
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