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EU-funded R&D project that aims to develop and validate a platform for composition of government services into complex process definitions (covering life events/business episodes) enabling semantic interoperability of particular e-Government services.
Agent based model of organizations considering the interplay between the formal hierarchical structure and the process network emerging while the organization performs a task-set.
Project includes: JRIO (drawing package), Lang (Java interpreter written in Java), and Cirrus (genetic and evolutionary algorithms, with evolvable virtual machine). Planned modules for entropy and information studies during an evolutionary process.
unEvo is an Eclipse plug-in that provides support for the experimentation and research process on Evolutionary Algorithms, intended so that the user can implement an evolutionary algorithm without lost time in the code of the algorithm.
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Spiritbot is a suite of tools designed for use in software-engineering, CodeGenUML includes an XMI/MOF/UML reader and exporter. An IRC ticker bot is also provided to aid in the development process.
JEOPS is a Java based forward chaining RULE ENGINE.
This Rule Engine is used to power up the business process by rules in Java Application Servers, client applications, and Servlets.
Agents design supporting system for simulation models
Main task is automating the creation of simulation models of complex model.
The originalities of proposed software are explicit representation of conceptual model in the concept – attribute – relation form and applying expert system approach to transform designed ontology into agent model. Researchers develop the structure and behavior of agents using declarative approach.
Web: https://84.237.20.67/RFFI/Main.php
Supertagging is a process of statistical lexical disambiguation, preprocessing step to parsing, which assigns LTAG tree categories to the lexical items present in the input sentence. Thus, if the input sentence is in the form of a dependency tree, the task of the supertagger is to assign the most probable TAG family to each node and edge in the dependency tree.