The Mario AI Benchmark and Competitions

a game-based benchmark for reinforcement learning algo-rithms and game AI techniques developed by the authors. The benchmark is based on a public domain clone of Nintendo’s classic platform game Super Mario Bros, and completely open source. During the last two years, the benchmark has been used in a number of competitions associated with international conferences, and researchers and students from around the world have contributed diverse solutions to try to beat the benchmark. The paper summarises these contributions, gives an overview of the state-of-art in Mario-playing AIs, and chronicles the development of the benchmark. This paper is intended as the definitive point of reference for those using the benchmark for research or teaching

Session S4H Fast and Reliable Plagiarism Detection System

Abstract – Plagiarism and similarity detection software is well-known in universities for years. Despite the variety of methods and approaches used in plagiarism detection, the typical trade-off between the speed and the reliability of the algorithm still remains. We introduce a new two-step approach to plagiarism detection that combines high algorithmic performance and the quality of pairwise file comparison. Our system uses fast detection method to select suspicious files only, and then invokes precise (and slower) algorithms to get reliable results. We show that the proposed method does not noticeably reduce the quality of the pairwise comparison mechanism while providing better speed characteristics. Index Terms – Plagiarism detection, similarity detection, string matching

Super Mario Evolution

Abstract — We introduce a new reinforcement learning benchmar