Konstantinos Giannakis

Dominant Strategies of Quantum Games on Quantum Periodic Automata

Game theory and its quantum extension apply in numerous fields that affect people’s social, political, and economical life. Physical limits imposed by the current technology used in computing architectures (e.g., circuit size) give rise to the need for novel mechanisms, such as quantum inspired computation. Elements from quantum computation and mechanics combined with game-theoretic aspects of computing could open new pathways towards the future technological era. This paper associates dominant strategies of repeated quantum games with quantum automata that recognize infinite periodic inputs. As a reference, we used the PQ-PENNY quantum game where the quantum strategy outplays the choice of pure or mixed strategy with probability 1 and therefore the associated quantum automaton accepts with probability 1. We also propose a novel game played on the evolution of an automaton, where players’ actions and strategies are also associated with periodic quantum automata.

Quantum automata for infinite periodic words

Quantum computing defines the use of quantum mechanics in the computation process. Given that Moores law is about to reach its physical limits, it is natural to search for new technologies and computation models. The need for mechanisms and verification processes for infinite quantum computation will draw the attention of the research community. Potential applications of the proposed automata concern the verification of quantum systems and the design of appropriate quantum circuits. In the present work we define a quantum version of ω-automata, the periodic quantum automata that are able to efficiently recognize ω-languages of the form (amb)ω, where m is a finite number. We present our definitions through examples and figures. Even if our definition is simple, yet it has several interesting and useful properties. For example, they seem to be space efficient for periodic ω-languages of the form (amb)ω.

Mitochondrial Fusion Through Membrane Automata

Studies have shown that malfunctions in mitochondrial processes can be blamed for diseases. However, the mechanism behind these operations is yet not sufficiently clear. In this work we present a novel approach to describe a biomolecular model for mitochondrial fusion using notions from the membrane computing. We use a case study defined in BioAmbient calculus and we show how to translate it in terms of a P automata variant. We combine brane calculi with (mem)brane automata to produce a new scheme capable of describing simple, realistic models. We propose the further use of similar methods and the test of other biomolecular models with the same behaviour.

User requirements for gamifying sports software

Sports tracking software for casual exercising has become popular with smart phone users who are concerned about their health and fitness. Nevertheless, there is limited research on the user requirements for sports tracking software, which needs to be fun and easy to use in order to appeal to a broad set of users. For this purpose, we employed a four-week long experiment with five users who were asked to perform multiple workouts with two levels of gamification. The first treatment stands for “no gamification” and the second treatment provided rich visual feedback, such as speed, distance, elapsed time, map. At the end of the experiment, we asked users to describe the devices. Both devices included GPS sensor, so we also measured the distance covered for each one of the workouts. We found that augmented feedback from mobile self-tracking devices can promote working out, but there is also a trade-off of increased anxiety and disorientation. Thus, we suggest that sports tracking software should be modest about how much and what type of visual information it provides to the user. In particular, we found that the only piece of visual information that had an impact on performance was average speed, which indicates a connection with gamication. Further research should consider additional levels of gamification beyond score, such as graphics, sociability, rules.

Web Mining to Create Semantic Content: A Case Study for the Environment

In this study, the goal is multifold. At first we present a summarized review of terms and facts regarding the branch of ecoinformatics, web mining and the semantic web. In Section 2 we provide some related work derived from the current literature upon the web mining and the production of semantic content. The main part of our work follows presenting a notional model for building semantic content through 2-level web mining. This is achieved in web sites containing environmental data. We conclude mentioning the importance of this contribution from different points of view.

Membrane automata for modeling biomolecular processes

Bioinspired computation models and mechanisms are widely used in various applications, both in theoretical and practical level. Membrane Computing, a branch of Natural Computing, is constantly producing interesting results the last 15 years. In this work we attempt to describe a mitochondrial fusion process based on membrane automata in a novel way. We combine these computation machines with notions from brane calculus and we depict the procedure of the production of specific proteins that are essential for a successful fusion. We also discuss possible extensions of our methodology stating direction for future works and thoughts.

Initialization methods for the TSP with Time Windows using Variable Neighborhood Search

This paper presents a General Variable Search heuristic, trying to discover initial, feasible solution for the Travelling Salesman Problem with Time Windows. More specifically, we provide all relevant information regarding TSP-TW, Variable Neighborhood Search (VNS) and initialization methods, then we quote all related work in the direction on solving this NP-HARD problem, and at last we propose our new implementation for generating initial, feasible solution for the TSP-TW. We are thoroughly focused on the behavior of our main algorithm to different random-based or sorting-based initialization procedures of our main implemented algorithm. At last, we show experimentally that in some cases, the use of a sorting function as an initialization function in this algorithm did not work and never returned a feasible solution in some cases.

Querying Linked Data and Büchi Automata

Linked Data is a field with ongoing development showing not only practical applications but also elegant theoretical results. Parts of these works concern the query process of Linked Data using SPARQL. Our work examines the querying of such data sources which are characterized by eventual computability, rather than finite. This infinite character of the data and the query process stimulated the use of Büchi automata in order to properly verify this computation model. In brief, our work contributes by presenting a novel approach to describe the infinite computation of SPARQL queries on a Web of Linked Data using Büchi automata.

Probabilistic flooding coverage analysis for efficient information dissemination in wireless networks

Abstract Information dissemination under Probabilistic flooding is revisited here in an attempt to realize full coverage in modern wireless networks and at the same time avoid unnecessary transmissions that waste valuable resources. Approaches like traditional flooding, are not suitable in these typically large scale and inherently dynamic environments due to the large number of transmitted information messages. Probabilistic flooding is capable of pruning unnecessary transmissions, while maintaining a large proportion of the network nodes covered. In this paper, an algebraic-based approach is employed to derive an estimation regarding the particular threshold probability value that would allow for high network coverage and reduced number of sent information messages. For the analysis’ purposes, coverage is studied here and eventually modeled as a polynomial; its higher root being related to the threshold probability. By studying this polynomial’s roots, the paper’s contribution is twofold: (i) results existing in the open literature are confirmed; and (ii) an algorithm is introduced here to estimate the threshold probability. Simulation results confirm the analytical findings and in addition, they demonstrate that the estimated value derived here regarding threshold probability, is suitable for achieving high coverage and reducing the number of transmitted information messages.

Associating ω-automata to path queries on Webs of Linked Data

The emergence of semantically enriched data sets along with the elegant way they are interconnected through the concept of Linked Data has drawn the attention of various scientific branches. The volume and the quality of information that lie inside the Linked Data, along with the capabilities they offer, make them ideal candidate to mine and extract valuable material, especially in field with great humanitarian importance, such as biology, medicine and social networks. As we show in this work, there are queries that cannot be expressed neither by standard SPARQL nor its expansion with regular path queries.These queries assume that the Web of Linked Data can be infinite and therefore classic queries expressed in terms of SPARQL need to be revisited. We propose a novel method associating a variant of automata that read infinite inputs, namely the ω-automata, to each query on this infinite structure. We call these queries ω-regular path queries due to the fact that they use ω-regular expressions. These expressions are of the form a | ( ab ) ω . We present our approach through examples and figures, mainly inspired from systems related to biological functions and processes, providing indicative queries.