Logic Programming, and the language Prolog in particular, has been proven to be very useful for the implementation of applications from various fields of Artificial Intelligence (e.g. Expert Systems, Machine Learning, Search, Reasoning, Planning, Natural Language Processing, Deductive Databases, Data Mining, etc) [1], [5]. One of the most dynamic programming paradigms nowadays is undoubtedly th...

The paper presents the mechanisms for dynamic load distribution implemented within the support for the Parallel Objects (PO for short) programming environment. PO applications evolve depending on their dynamic need of resources, enhancing application performance. The goal is to show how dynamic load distribution can be successfully applied on a massively parallel architecture.

The demo presents an optical flow computation technique based on dynamic programming, its results on the Fleet, Barron and Beauchemin benchmark, and its application to: 3D reconstruction, time interpolation of image sequences using motion information, particle image velocimetry and segmentation of video sequences into shots.

In this paper, we propose a scheme called Hierarchically Accelerated Dynamic Programming (HADP) which gives signiicant speed up of Dynamic Programming (up to several orders of magnitude) for Discrete Event Systems (DES) modelled by nite state machines: this is at the cost of a degree of sub-optimality. This methodology is based upon a dynamical abstraction of the given DES by state aggregation ...