Search results for "Edge based"
showing 10 items of 36 documents
A new frontier in novelty detection: Pattern recognition of stochastically episodic events
2011
Published version of an article from the book: Intelligent Information and Database Systems, Lecture Notes in Computer Science. Also available from the publisher on SpringerLink:http://dx.doi.org/10.1007/978-3-642-20039-7_44 A particularly challenging class of PR problems in which the, generally required, representative set of data drawn from the second class is unavailable, has recently received much consideration under the guise of One-Class (OC) classification. In this paper, we extend the frontiers of OC classification by the introduction of a new field of problems open for analysis. In particular, we note that this new realm deviates from the standard set of OC problems based on the fo…
Using artificial intelligence techniques for strategy generation in the Commons game
2011
Published version of a chapter in the book: Hybrid Artificial Intelligent Systems. Also available from the publisher on SpringerLink: http://dx.doi.org/10.1007/978-3-642-21219-2_7 In this paper, we consider the use of artificial intelligence techniques to aid in discovery of winning strategies for the Commons Game (CG). The game represents a common scenario in which multiple parties share the use of a self-replenishing resource. The resource deteriorates quickly if used indiscriminately. If used responsibly, however, the resource thrives. We consider the scenario one player uses hill climbing or particle swarm optimization to select the course of action, while the remaining N − 1 players us…
Automatic Categorization of Web Sites
2008
Masteroppgave i informasjons- og kommunikasjonsteknologi 2008 – Universitetet i Agder, Grimstad In this thesis we have presented a solution to classify websites into geographical attribute code (NUTS) and economical activities attribute codes(NACE). We propose a solution for web site classification with high accuracy. We use keywordbased document classification methods which had shown good performance. After classification, each document is assigned a class label from a set of predefined categories, which is based on a pool of pre-classified sample documents. Our solution includes to remove stop words and skip html tags, which identify the informative term, remove the non-informative or red…
Finding Optimal Rush Attacks in Real Time Strategy (RTS) Games
2008
Masteroppgave i informasjons- og kommunikasjonsteknologi 2008 – Universitetet i Agder, Grimstad What will you fell when play with an unchangeable AI in RTS game? Of cause, it is boring. You can beat them easily and that’s no fun. In this research, we will try to design an AI with learning-ability and return the fun to players. We firstly abstract a simple AI mode, and then implement a suitable learning method . Due to some developing problems, we simulate the system (ORTS). Finally, we establish a new learning system for RTS AI. It’s an advanced point system based on the conception of the evaluation system in commercial RTS game . Decision making processes could depend on the points of each…
Hvorfor har det vist seg så komplisert å etablere informasjonsportaler i akademiske institusjoner : casestudie fra Handelshøjskolen i København og Un…
2008
Masteroppgave i informasjonssystemer - Universitetet i Agder 2008 Da prosjektene jeg har undersøkt ble påbegynt i 2003 var dette helt i starten på en bølge systemer som ble kalt Content Management Systems (CMS). Disse systemene skulle ta over og løse mange av de problemene som tradisjonelle filstrukturbaserte nettsteder hadde og har hatt siden tidlig på 1990 tallet. På den samme tiden var det liten erfaring fra andre implementasjoner som en kunne støtte seg på. Det var heller ikke gjort mye forskning på området da en ikke hadde tilgang til empiriske data (Nordheim 2004) som kunne forklare hva det innebar å etablere CMS løsninger. I dag begynner det å komme rapporterte erfaringer og det er t…
Brukerstøtte for programvare ved store og mellomstore bedrifter
2008
Masteroppgave i informasjonssystemer - Universitetet i Agder 2008 Formålet med denne oppgaven er å kaste lys over hvordan organisering av programvaresupport og brukerstøtte kan håndteres, samt bakgrunnen for denne organiseringen – uavhengig om den er et ledd i en formell supportplan eller uformelle vaner som har utviklet seg til de facto rutiner. Vi har også, noe overfladisk, sett dette i forhold til andre virksomhetsspesifikke forhold. Datainnsamlingen har fulgt en kvalitativ metode, og vi har gjennomført fem intervjuer med fire forskjellige virksomheter. Ellers har vi også brukt egne erfaringer i en av virksomhetene vi har arbeidet mot. Virksomhetene ble valgt etter et ønske om å få et vi…
Learning automata-based solutions to the optimal web polling problem modelled as a nonlinear fractional knapsack problem
2011
Accepted version of an article from the journal: Engineering Applications of Artificial Intelligence. Definitive published version on Elsevier Science Direct: http://dx.doi.org/10.1016/j.engappai.2011.05.018 We consider the problem of polling web pages as a strategy for monitoring the world wide web. The problem consists of repeatedly polling a selection of web pages so that changes that occur over time are detected. In particular, we consider the case where we are constrained to poll a maximum number of web pages per unit of time, and this constraint is typically dictated by the governing communication bandwidth, and by the speed limitations associated with the processing. Since only a fra…
Service selection in stochastic environments: a learning-automaton based solution
2011
Published version of an article from the journal: Applied Intelligence. Also available from the publisher on SpringerLink: http://dx.doi.org/10.1007/s10489-011-0280-5 In this paper, we propose a novel solution to the problem of identifying services of high quality. The reported solutions to this problem have, in one way or the other, resorted to using so-called “Reputation Systems” (RSs). Although these systems can offer generic recommendations by aggregating user-provided opinions about the quality of the services under consideration, they are, understandably, prone to “ballot stuffing” and “badmouthing” in a competitive marketplace. In general, unfair ratings may degrade the trustworthine…
Optimal “anti-Bayesian” parametric pattern classification for the exponential family using Order Statistics criteria
2012
Published version of a chapter in the book: Image Analysis and Recognition. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31295-3_2 This paper reports some pioneering results in which optimal parametric classification is achieved in a counter-intuitive manner, quite opposed to the Bayesian paradigm. The paper, which builds on the results of [1], demonstrates (with both theoretical and experimental results) how this can be done for some distributions within the exponential family. To be more specific, within a Bayesian paradigm, if we are allowed to compare the testing sample with only a single point in the feature space from each class, the optimal Bayesian strat…
On using prototype reduction schemes to optimize locally linear reconstruction methods
2012
Authors version of an article published in the journal: Pattern Recognition. Also available from the publisher at: http://dx.doi.org/10.1016/j.patcog.2011.06.021 This paper concerns the use of prototype reduction schemes (PRS) to optimize the computations involved in typical k-nearest neighbor (k-NN) rules. These rules have been successfully used for decades in statistical pattern recognition (PR) [1,15] applications and are particularly effective for density estimation, classification, and regression because of the known error bounds that they possess. For a given data point of unknown identity, the k-NN possesses the phenomenon that it combines the information about the samples from a pri…