Random problem distributions have played a key role in the study and design of algorithms for constraint satisfaction and Boolean satisfiability, as well as in our understanding o...
The increasing levels of system integration in Multi-Processor System-on-Chips (MPSoCs) emphasize the need for new design flows for efficient mapping of multi-task applications o...
The constraint paradigm provides powerful concepts to represent and solve different kinds of planning problems, e. g. factory scheduling. Factory scheduling is a demanding optimiz...
Software agents help automate a variety of tasks including those involved in buying and selling products over the Internet. Although shopping agents provide convenience for consume...
A distributed search algorithm for solving distributed constraint satisfaction problems (DisCSPs) is presented. The proposed algorithm is composed of multiple search processes (SP...