Renewal of intelligent decision support systems laboratory

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Due to scales and complexities of today's software, their critical roles and hence reliabilities required, and due to technological advances in computer chips and networking, it has become both necessary and possible to solve a complex problem in a large domain by a set of cooperating computers, called agents.  Depending on applications, agents need to determine what is the state of their domain based on uncertain local knowledge and observations (distributed probabilistic reasoning), or identify whether a global solution exists which satisfies their local constraints and if so find such a solution (distributed constraint satisfaction), or decide what is the joint action that would bring their environment to a most desirable state in the face of uncertainty (distributed decision making).      The Intelligent Decision Support Systems Laboratory that I founded 9 years ago studies how to build multiagent systems that are capable of distributed probabilistic reasoning, distributed constraint satisfaction, and distributed decision making.  Agent knowledge representation that we focus on is multiagent graphical models, and performance issues that we emphasize are theoretical soundness and computational efficiency.  Multiagent algorithms for performing these tasks are designed and analyzed, and prototypes (currently distributed to registered users in 30 countries) are implemented and tested.   To acquire graphical models needed by agents to perform their tasks, knowledge discovery from data and elicitation from expert are also investigated in the lab.    The last major purchase of computing equipment in the lab was in 2001. Due to advancement in chip technology, performance of the existing equipment is now falling behind.  The requested equipment will renew the lab with the state of the art computing equipment to support design and evaluation of new algorithms and development of prototype systems.