Given a strongly stationary Markov chain and a finite set of stopping rules, we prove the existence of a polynomial algorithm which projects the Markov chain onto a minimal Markov chain without redundant information. Markov complexity is hence defined and tested on some classical problems.

Given a strongly stationary Markov chain and a finite set of stopping rules, we prove the existence of a polynomial algorithm which projects the Markov chain onto a minimal Markov chain without redundant information. Markov complexity is hence defined and tested on some classical problems.

In this paper we present and evaluate a general framework for the design of truthful auctions for matching agents in a dynamic, two-sided market. A single commodity, such as a resource or a task, is bought and sold by multiple buyers and sellers that arrive and depart over time. Our algorithm, Chain, provides the first framework that allows a truthful dynamic double auction (DA) to be construct...

Markov chains are awesome and can solve some important computational problems. A classic example is computing the volume of a convex body, where Markov chains and random sampling provide the only known polynomial time algorithm. Arguably the most important question about a Markov chain is how long to run it until it converges to its stationary distribution. Generally, a chain is run for some fi...

We develop a new method for placing a given context-free grammar into Greibach normal form with only polynomial increase of its size. Starting with an arbitrary "-free context-free grammar G, we transform G into an equivalent context-free grammar H in extended Greibach normal form; i.e., in addition to rules, fulllling the Greibach normal form properties, the grammar can have chain rules. The s...

Rule-based machine translation analyzes source-language sentences using large-scale linguistic knowledge that is given by the developer beforehand. However, it is difficult to give complete linguistic knowledge to the system ex ante because natural language has various linguistic phenomena. Therefore, we worked to develop learning-based machine translation. In learning-based machine translation...

Generalized communicating P systems (GCPSs) are purely communicating tissue-like membrane systems with rules for moving pairs of objects. Despite their simplicity, these systems are rather powerful, they are able to generate any recursively enumerable set of numbers even having restricted variants of communication rules. In this paper we show that GCPSs still remain computationally complete if ...

As one of the key techniques in multi-representation database, GIS, mapmaking and Digital Earth, automatic cartographic generalization has been intensively researched since decades. Current developments worldwide have been concentrated on the efforts towards adaptive and easily embeddable automatic generalization modules or services. Based on an analysis of the common rules concerning the quali...