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Read e-book online AI*IA 2005: Advances in Artificial Intelligence: 9th PDF

By Stefania Bandini, Sara Manzoni

This ebook constitutes the refereed court cases of the ninth Congress of the Italian organization for man made Intelligence, AI*IA 2005, held in Milan, Italy in September 2005.

The forty six revised complete papers provided including sixteen revised brief papers have been rigorously reviewed and chosen for inclusion within the ebook. The papers are equipped in topical sections on both theoretical study with effects and suggestions, advancements and consolidations, or on purposes as there are structures and prototypes, case stories and recommendations. inside this category a few of the major classical subject matters of AI are offered (agents, wisdom illustration, laptop studying, making plans, robotics, ordinary language, etc.), yet right here the focal point is at the skill of AI computational ways to stand tough difficulties and to suggest cutting edge suggestions.

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Johnson. Computers and intractability; a guide to the theory of NPcompleteness. H. Freeman, 1979. 10. S. Prestwich and A. Roli. Symmetry breaking and local search spaces. In Proceedings of CPAIOR 2005, volume 3524 of Lecture Notes in Computer Science. Springer–Verlag, 2005. 11. I. Rish and R. Dechter. Resolution versus search: Two strategies for SAT. J. Automated Reasoning, 24:225–275, 2000. 12. A. Roli. Criticality and parallelism in GSAT. Electronic Notes in Discrete Mathematics, 9, 2001. 24 A.

Small-world SAT instances are constructed by introducing clauses from random instances into lattice based ones. 3 4 The 800-2400 instances are indeed not solved by GSAT in the range corresponding to smallworld. This observation is also confirmed by evaluating a moving window average. On the Impact of Small-World on Local Search 23 We tackled the benchmark instances with three different local search algorithms and observed their behavior across the whole spectrum, from regular lattice to random topologies.

Search cost of GSAT across the instances, from lattice to random structure. In the uppermost left plot, points represent median iterations over 1000 runs. , the number of instances solved – given a termination condition defined as the maximum number of non-improving moves. evaluated as number of variable assignments performed by the algorithm before solving the instance, is the highest). Results are shown in Figs. 9, 10 and 11. In the plots, we reported for each algorithm the median iterations (over 1000 runs) on every instance.

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