Search results for "ComputingMethodologies_ARTIFICIALINTELLIGENCE"
showing 10 items of 46 documents
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.
Ant Colony Models for a Virtual Educational Environment Based on a Multi-Agent System
2008
We have designed a virtual learning environment where students interact through their computers and with the software agents in order to achieve a common educational goal. The Multi-Agent System (MAS) consisting of autonomous, cognitive and social agents communicating by messages is used to provide a group decision support system for the learning environment. Learning objects are distributed in a network and have different weights in function of their relevance to a specific educational goal. The relevance of a learning object can change in time; it is affected by students', agents' and teachers' evaluation. We have used an ant colony behavior model for the agents that play the role of a tu…
Using Semantics in the Environment for Multiagent-Based Simulation
2014
In this chapter, we carry out an overview and analysis of the usage of semantics to enhance environments in the domain of multiagent-based simulations. Firstly, we take a look at what a multiagent system (MAS) is, and after that we look at the environment for these systems, and why semantics are required in it. Various propositions to put semantics in the environment for MAS are then reviewed, as well as the strengths and weaknesses for these approaches. These propositions are grouped together under two categories, regarding whether the proposed approach is based on only the environment or on both the agents and the environment. The paper is then concluded with findings that have emerged by…
Fuzzy predictive controller design using ant colony optimization algorithm
2014
In this paper, an approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the Ant Colony Optimization (ACO) is studied. On-line adaptive fuzzy identification is used to identify the system parameters. These parameters are used to calculate the objective function based on predictive approach and structure of RST control. The optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to calculate a sequence of future RST control actions. The obtained simulation results show that proposed approach provides better results compared with Proportional Integral-Ant Colony Optimization (PI-ACO) controller and adaptive fuzzy model pr…
A virtual testbed for analysis and design of sensorimotoric aspects of agent control
1997
Abstract In this paper XRaptor is introduced, an object-oriented simulation tool. It provides a virtual multi-agent world which acts as testbed for agent control mechanisms. This environment encompasses a 3-dimensional space, in which the agents may move. Currently agents are realized modelling some abstract properties of flies and bats. XRaptor provides different levels of information flow and world manipulation capabilities from the agents' point of view. A further purpose of XRaptor is educational: Different teams of developers may design control units for agents which can then be subjected to a tournament.
A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics
2006
We propose a new distributed image segmentation algorithm structured as a multiagent system composed of a set of segmentation agents and a coordinator agent. Starting from its own initial image, each segmentation agent performs the iterated conditional modes method, known as ICM, in applications based on Markov random fields, to obtain a sub-optimal segmented image. The coordinator agent diversifies the initial images using the genetic crossover and mutation operators along with the extremal optimization local search. This combination increases the efficiency of our algorithm and ensures its convergence to an optimal segmentation as it is shown through some experimental results.
Fine-tuning the Ant Colony System algorithm through Particle Swarm Optimization
2018
Ant Colony System (ACS) is a distributed (agent- based) algorithm which has been widely studied on the Symmetric Travelling Salesman Problem (TSP). The optimum parameters for this algorithm have to be found by trial and error. We use a Particle Swarm Optimization algorithm (PSO) to optimize the ACS parameters working in a designed subset of TSP instances. First goal is to perform the hybrid PSO-ACS algorithm on a single instance to find the optimum parameters and optimum solutions for the instance. Second goal is to analyze those sets of optimum parameters, in relation to instance characteristics. Computational results have shown good quality solutions for single instances though with high …
PESI - a taxonomic backbone for Europe
2015
Reliable taxonomy underpins communication in all of biology, not least nature conservation and sustainable use of ecosystem resources. The flexibility of taxonomic interpretations, however, presents a serious challenge for end-users of taxonomic concepts. Users need standardised and continuously harmonised taxonomic reference systems, as well as highquality and complete taxonomic data sets, but these are generally lacking for nonspecialists. The solution is in dynamic, expertly curated web-based taxonomic tools. The Pan-European Species-directories Infrastructure (PESI) worked to solve this key issue by providing a taxonomic e-infrastructure for Europe. It strengthened the relevant social (…