Search results for "Lint"
showing 10 items of 1609 documents
Exploring citizens' legitimacy judgments about governmental refugee policies
2017
Tämän tutkimuksen tavoitteena on saada tietoa siitä, miten nuoret, korkeakoulutetut suomalaiset muodostavat legitimiteettiarvioitaan Suomen hallituksen pakolaispolitiikasta. Tutkimus on osa kansainvälistä tutkimushanketta, joka toteutettiin Suomessa, Saksassa ja Espanjassa. Työn teoreettinen viitekehys on legitimiteettiteoriassa ja erityisesti Suchmanin (1995) neljässä legitimiteetin alatyypissä. Tutkimusmetodeina käytetään fokusryhmätutkimusta, Q-metodia ja teoriaohjaavaa sisällönanalyysia. Tulokset osoittavat luottamusta hallituksen toimia kohtaan pakolaiskriisissä. Tämän tutkimuksen perusteella Suomen hallitukselle myönnetään legitimiteetti sen pohjalta, miten hallit…
Recursive and bargaining values
2021
Abstract We introduce two families of values for TU-games: the recursive and bargaining values. Bargaining values are obtained as the equilibrium payoffs of the symmetric non-cooperative bargaining game proposed by Hart and Mas-Colell (1996). We show that bargaining values have a recursive structure in their definition, and we call this property recursiveness. All efficient, linear, and symmetric values that satisfy recursiveness are called recursive values. We generalize the notions of potential, and balanced contributions property, to characterize the family of recursive values. Finally, we show that if a time discount factor is considered in the bargaining model, every bargaining value h…
Cryptanalysis of Knapsack Cipher Using Ant Colony Optimization
2018
Ant Colony Optimization is a search metaheuristic inspired by the behavior of real ant colonies and shown their effectiveness, robustness to solve a wide variety of complex problems. In this paper, we present a novel Ant Colony Optimization (ACO) based attack for cryptanalysis of knapsack cipher algorithm. A Cipher-text only attack is used to discover the plaintext from the cipher-text. Moreover, our approach allows us to break knapsack cryptosystem in a minimum search space when compared with other techniques. Experimental results prove that ACO can be used as an effective tool to attack knapsack cipher.
Optimizing PolyACO Training with GPU-Based Parallelization
2016
A central part of Ant Colony Optimisation (ACO) is the function calculating the quality and cost of solutions, such as the distance of a potential ant route. This cost function is used to deposit an opportune amount of pheromones to achieve an apt convergence, and in an active ACO implementation a significant part of the runtime is spent in this part of the code. In some cases, the cost function accumulates up towards 94 % in its run time making it a performance bottle neck.
An introduction to knowledge computing
2014
This paper deals with the challenges related to self-management and evolution of massive knowledge collections. We can assume that a self-managed knowledge graph needs a kind of a hybrid of: an explicit declarative self-knowledge (as knowledge about own properties and capabilities) and an explicit procedural self-knowledge (as knowledge on how to utilize own properties and the capabilities for the self-management).We offer an extension to a traditional RDF model of describing knowledge graphs according to the Semantic Web standards so that it will also allow to a knowledge entity to autonomously perform or query from remote services different computational executions needed. We also introdu…
OWL2: The Next Step for OWL
2008
Since achieving W3C recommendation status in 2004, the Web Ontology Language (OWL) has been successfully applied to many problems in computer science. Practical experience with OWL has been quite positive in general; however, it has also revealed room for improvement in several areas. We systematically analyze the identied short-comings of OWL, such as expressivity issues, problems with its syntaxes, and deficiencies in the definition of OWL species. Furthermore, we present an overview of OWL 2 -- an extension to and revision of OWL that is currently being developed within the W3C OWL Working Group. Many aspects of OWL have been thoroughly reengineered in OWL 2, thus producing a robust plat…
A Direct Approach to Robot Soccer Agents: Description for the Team Mainz Rolling rains Simulation League of RoboCup ’98
1999
In the team described in this paper we realize a direct approach to soccer agents for the simulation league of the RoboCup '98- tournament. Its backbone is formed by a detailed world model. Based on information which is reconstructed on the world model level, the rule-based decision levels chose a relevant action. The architecture for the goalie is different from the regular players, introducing heterogeneousness into the team, which combines the advantages of the different control strategies.
Chat Agents Tutoring System
2004
In this paper we present a Multi Agent tutoring dialogue system. The Chat Agent Tutoring System is an attempt to produce incremental gains in learning using a community of chat agents, which have specific competences and are able to carry out natural language conversation. The system has been developed by integrating two emerging technologies: Java Agent Development Environment (JADE) and ALICE technology.
Building a Maturity Model for Developing Ethically Aligned AI Systems
2021
Ethical concerns related to Artificial Intelligence (AI) equipped systems are prompting demands for ethical AI from all directions. As a response, in recent years public bodies, governments, and companies have rushed to provide guidelines and principles for how AI-based systems are designed and used ethically. We have learned, however, that high-level principles and ethical guidelines cannot be easily converted into actionable advice for industrial organizations that develop AI-based information systems. Maturity models are commonly used in software and systems development companies as a roadmap for improving the performance. We argue that they could also be applied in the context of develo…
Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations
2022
AbstractWe introduce novel concepts to solve multiobjective optimization problems involving (computationally) expensive function evaluations and propose a new interactive method called O-NAUTILUS. It combines ideas of trade-off free search and navigation (where a decision maker sees changes in objective function values in real time) and extends the NAUTILUS Navigator method to surrogate-assisted optimization. Importantly, it utilizes uncertainty quantification from surrogate models like Kriging or properties like Lipschitz continuity to approximate a so-called optimistic Pareto optimal set. This enables the decision maker to search in unexplored parts of the Pareto optimal set and requires …