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Simulation Balancing is an optimization algorithm to automatically tune the parameters of a playout policy used inside a Monte Carlo Tree Search. The algorithm fits a policy so that the expected result of a policy matches given target values of the training set. Up to now it has been successfully applied to Computer Go on small 9 × 9 boards but failed for larger board sizes like 19 × 19. On these...
In Monte Carlo Tree Search often extra knowledge in form of patterns is used to guide the search and improve the playouts. Shape patterns, which are frequently used in Computer Go, do not describe tactical situations well, so that this knowledge has to be added manually. This is a tedious process which cannot be avoided as it leads to big improvements in playing strength. The common fate graph, which...
This paper introduces a 3D-stacked logic-in-memory (LiM) system to accelerate the processing of sparse matrix data that is held in a 3D DRAM system. We build a customized content addressable memory (CAM) hardware structure to exploit the inherent sparse data patterns and model the LiM based hardware accelerator layers that are stacked in between DRAM dies for the efficient sparse matrix operations...
Swarm robots provide greater flexibility and robust performance in tasks such as sensing and monitoring of unstructured and unpredictable environments. They need to self-deploy in these environments maximizing coverage and maintaining network connectivity for efficient operation. Inspired from nature, we design a new algorithm based on simple local rules, which achieves coverage and connectivity as...
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