This infrastructure award is for the purchase of a network of high speed workstations. This network of workstations is to support research in artificial intelligence, programming languages, geometric computing, and fault tolerant computing. The artificial intelligence research is concentrated in four areas: machine learning, constraint satisfaction networks, parallel logic programming, and knowledge representation. The research in programming languages involves the translation of CCS specifications to an implementation language which provably implements concurrency and provably satisfies real time constraints. The research in geometric computing is focused on computing higher-degree curves and surfaces, alternate representations for curves and surfaces, efficient methods for representing geometric modes, and motion planning. The research in fault tolerant computing is concentrated on self-monitoring systems. Johns Hopkins University will use its infrastructure grant to improve the environment for experimental research in computer science, information science, and computer engineering. Artificial intelligence is the generic name given to computer based research on performing actions normally described as "intelligent actions." Johns Hopkins researchers will explore learning and reasoning actions. Languages to instruct computers in their operations have been studied for many years. The goal of these languages is to succinctly describe the desired operation with as little error as possible. The programming language research at Johns Hopkins pursues this goal for systems that must respond in "real time". Computers are used extensively in robots. In order for reasoning to be performed about the environment in which the robot resides, a mathematical model of that environment must be constructed. Johns Hopkins researchers will be studying how to construct and use better mathematical models. Finally, the network as a whole will be used as a test bed for algorithms to detect faulty computers or links on the network.
