Non-deterministic imperfect information games pose challenges for Artificial Intelligence (AI) design, as compared to AI for perfect information games. Monte Carlo Tree Search (MCTS), an AI technique that uses random sampling of game playouts to build a search tree rather than domain-specific knowledge about how to play a given game, has been used successfully in some perfect information games. MCTS has also been implemented for imperfect information board and card games, using techniques including sampling over many determinizations of a starting game state, and considering which information set each player belongs to. In this paper, we first describe the imperfect information card game Cribbage and the MCTS algorithm. We then describe our implementation of Cribbage for two players and several MCTS and non-MCTS-based AI players. We compare their performance and find that Single-Observer Information Set MCTS performs well in this domain.
Self-organizing maps have been used for several decades as an artificial neural network model for dimension reduction of high-dimensional data for the purposes of data clustering and visualization. In this paper, we propose a new data clustering method inspired from the self-organizing map. Unlike the self-organizing map, we propose a pre-clustering phase for our method that uses Euclidean distance and cosine similarity. Once data are pre-clustered, this method uses an unsupervised learning phase (training phase), which is similar to the training phase for self-organizing maps. Unlike traditional self-organizing maps, the proposed algorithm does not use a map at all, mitigating the issues associated with its use. The method is also highly-parallelizable which allows for a GPU implementation. Results demonstrating the excellent performance of the proposed clustering algorithm are included in this paper.
Abstract-Choosing an efficient programming language is a substantial challenge in software development. Several factors should be considered while investigating programming languages; one of the most significant factors is the importance of secure programming. For programmers concerned with application security, the features provided by each language to support secure coding are important to understand. In this paper we discuss secure programming practices in Java and C++, briefly considering their major differences, capabilities and limitations. Index Terms---Software vulnerability, secure programming, memory safety, Java programming, C++ programming.
