Download KI 2008: Advances in Artificial Intelligence: 31st Annual by Randy Goebel (auth.), Andreas R. Dengel, Karsten Berns, PDF

By Randy Goebel (auth.), Andreas R. Dengel, Karsten Berns, Thomas M. Breuel, Frank Bomarius, Thomas R. Roth-Berghofer (eds.)

This publication constitutes the completely refereed court cases of the 31th Annual German convention on man made Intelligence, KI 2008, held in Kaiserslautern, Germany, September 2008.

The 15 revised complete papers awarded including 2 invited contributions and 30 posters have been rigorously reviewed and chosen from seventy seven submissions. The papers disguise very important parts comparable to trend reputation, multi-agent platforms, computer studying, traditional language processing, constraint reasoning, wisdom illustration and administration, making plans, and temporal reasoning.

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Extra resources for KI 2008: Advances in Artificial Intelligence: 31st Annual German Conference on AI, KI 2008, Kaiserslautern, Germany, September 23-26, 2008. Proceedings

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In general they are not able to guarantee that all such potential hazards can be found, though. A full verification usually involves induction and therefore can hardly be fully automatic. Therefore the definition and application of suitable heuristics has turned out to become a central necessity. This paper describes how we attack this problem with the help of the Verification Support Environment (VSE) and how we nevertheless arrive at a high degree of automation. 1 Introduction Protocols that (try to) provide certain security properties in open network environments by using cryptographic primitives like encryption, signing, and hashing, play a crucial role in many emerging application scenarios.

In this paper we focus on the techniques we developed to adopt Paulson’s approach for the Verification Support Environment (VSE). VSE is a kind of case tool for formal software development that closely combines a front end for specification (including refinement) and the management of structured developments with an interactive theorem prover [4]. We emphasize on our attempt to lower the burden of interactive proof generation to an extent that makes the VSE framework for protocol verification applicable within the limited time frames of commercial developments.

Xn . , xk } for the entire video database. , xk } a feature vector zi ∈ RD is extracted. A common way to extract keyframes for each video is to segment the data into shots and analyze the shots individually for representative keyframes. We use a divide-and-conquer approach that delivers multiple keyframes per shot in respect to its visual complexity. To achieve this, we compute MPEG-7 color layout descriptors [14] for each frame of the shot and fit a Gaussian mixture model to the feature set using k-means [15] in combination with the Bayesian Information Criterion (BIC) for determining the number of clusters.

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