Mitsuo Wakatsuki

A simple and faster branch-and-bound algorithm for finding a maximum clique

This paper proposes new approximate coloring and other related techniques which markedly improve the run time of the branch-and-bound algorithm MCR (J. Global Optim., 37, 95–111, 2007), previously shown to be the fastest maximum-clique-finding algorithm for a large number of graphs. The algorithm obtained by introducing these new techniques in MCR is named MCS. It is shown that MCS is successful in reducing the search space quite efficiently with low overhead. Consequently, it is shown by extensive computational experiments that MCS is remarkably faster than MCR and other existing algorithms. It is faster than the other algorithms by an order of magnitude for several graphs. In particular, it is faster than MCR for difficult graphs of very high density and for very large and sparse graphs, even though MCS is not designed for any particular type of graphs. MCS can be faster than MCR by a factor of more than 100,000 for some extremely dense random graphs.

Polynomial time learning of simple deterministic languages via queries and a representative sample

We show that simple deterministic languages are polynomial time learnable via membership queries if the learner knows a special finite set of positive examples. This finite set is called a representative sample and has been introduced by Angluin Inform. Control 51 (1981) to show that regular languages are polynomial time learnable via membership queries. If simple deterministic languages are learnable in polynomial time via membership and equivalence queries, we can obtain a representative sample of a target language in polynomial time from a correct hypothesis. Thus, our result implies that the polynomial time learning problem of simple deterministic languages via membership and equivalence queries is solvable if and only if we can find a representative sample in polynomial time via these queries. We show the learnability of simple deterministic languages by giving a learning algorithm. The algorithm, at the first stage, makes all possible candidate rules to generate the target language and a set of simple deterministic grammars which are little different each other. Then, comparing them, the algorithm eliminates inappropriate rules.

A Much Faster Branch-and-Bound Algorithm for Finding a Maximum Clique

We present improvements to a branch-and-bound maximum-clique-finding algorithm MCS (WALCOM 2010, LNCS 5942, pp. 191–203) that was shown to be fast. First, we employ an efficient approximation algorithm for finding a maximum clique. Second, we make use of appropriate sorting of vertices only near the root of the search tree. Third, we employ a lightened approximate coloring mainly near the leaves of the search tree. A new algorithm obtained from MCS with the above improvements is named MCT. It is shown that MCT is much faster than MCS by extensive computational experiments. In particular, MCT is shown to be faster than MCS for gen400_p0.9_75 and gen400_p0.9_65 by over 328,000 and 77,000 times, respectively.

A Source Code Plagiarism Detecting Method Using Sequence Alignment with Abstract Syntax Tree Elements

Learning to program is an important subject in computer science courses. During programming exercises, plagiarism by copying and pasting can lead to problems for fair evaluation. Some methods of plagiarism detection are currently available, such as sim. However, because sim is easily influenced by changing the identifier or program statement order, it fails to do enough to support plagiarism detection. In this paper, the authors propose a plagiarism detection method which is not influenced by changing the identifier or program statement order. The authors also explain our method’s capabilities by comparing it to the sim plagiarism detector. Furthermore, the authors reveal how our method successfully detects the presence of plagiarism. A Source Code Plagiarism Detecting Method Using Sequence Alignment with Abstract Syntax Tree Elements

A source code plagiarism detecting method using alignment with abstract syntax tree elements

Learning to program is an important subject in computer science courses. During programming exercises, plagiarism by copying and pasting can lead to problems for fair evaluation. Some methods of plagiarism detection are currently available, such as sim. However, because sim is easily influenced by changing the identifier or program statement order, it fails to do enough to support plagiarism detection. In this paper, we propose a plagiarism detection method which is not influenced by changing the identifier or program statement order. We also explain our methods capabilities by comparing it to the sim plagiarism detector. Furthermore, we reveal how our method successfully detects the presence of plagiarism.

A Polynomial-Time Algorithm for Checking the Equivalence for Real-Time Deterministic Restricted One-Counter Transducers Which Accept by Final State

This paper is concerned with a subclass of deterministic pushdown transducers, called deterministic restricted one-counter transducers (drocts), and studies the equivalence problem for real-time drocts which accept by final state. After providing some properties of these drocts, we present a polynomial-time algorithm for checking the equivalence for these drocts.

Polynomial time identification of strict prefix deterministic finite state transducers

This paper is concerned with a subclass of finite state transducers, called strict prefix deterministic finite state transducers (SPDFSTs for short), and studies a problem of identifying the subclass in the limit from positive data. After providing some properties of languages accepted by SPDFSTs, we showthat the class of SPDFSTs is polynomial time identifiable in the limit from positive data in the sense of Yokomori.

Decision Tree Analysis in Game Informatics

Computer Daihinmin involves playing Daihinmin, a popular card game in Japan, by using a player program. Because strong player programs of Computer Daihinmin use machine-learning techniques, such as the Monte Carlo method, predicting the program’s behavior is difficult. In this study, we extract the features of the player program through decision tree analysis. The features of programs are extracted by generating decision trees based on three types of viewpoints. To show the validity of our method, computer experiments were conducted. We applied our method to three programs with relatively obvious behaviors, and we confirmed that the extracted features were correct by observing real behaviors of the programs.

A Polynomial-Time Algorithm for Checking the Equivalence of Deterministic Restricted One-Counter Transducers Which Accept by Final State

This paper is concerned with a subclass of deterministic pushdown transducers, called deterministic restricted one-counter transducers (droct’s), and studies the equivalence problem for droct’s which accept by final state. In the previous study, we presented a polynomial-time algorithm for checking the equivalence of real-time droct’s. By extending the technique, we present a polynomial-time algorithm for checking the equivalence of non-real-time droct’s.

A unified algorithm for extending classes of languages identifiable in the limit from positive data

We are concerned with a unified algorithm for extending classes of languages identifiable in the limit from positive data. Let