A method for tuning parameters under a fixed time constraint for a general binocular stereo-vision algorithm is presented. TEACHER 4.2, a generate-and-test system that systematically generates new parameter values by analyzing the results of previous tests and performs limited and controlled tests on the candidates generated using high-speed computers, is discussed. The system is modeled as a statistical selection problem operating under a given time constraint. Results show that the system can find new parameter-value sets which in some cases are better than the ones originally found by extensive hand-tuning and commonly used heuristics, and that different parameter values may be required under different objectives and performance constraints.>

In this paper we present TEACHER 4.1, a system for designing automatically heuristics that map a set of cmnmunicating processes on a real-time distributed computing system.The problem of optimal promas mapping is NP-hard and involves the optimal placement of precesses on the distributed system and the optimaf routing of messages from one computer to another.The design of efficient and robust heuristics is often ad hoc and is guided by intuition and experience of the designers.In this paper we develop a statistical method to explore systematically the space of possible heuristics for process mapp.mg.The method operates under a specified time constraint and intends to get the best possible heuristics whale trading between the solution quality and the execution time of the process mapping heuristics.Our prototype for process mWPing is extended hom post-game analysis, a system that uses a set of user-specified roles for generating new mappings.It tunes pamneters of these rules and proposea new heuristics for process mapping.Simulations show that there is significant improvement m performance through systematic and automatic exploration of the spare of heuristics.