The Coordination of interdependencies between tasks in collaborative environments is a very important and difJicult endeavor. The separation between tasks and interdependencies allows f o r the use of different coordination policies in the same collaborative environment by changing only the coordination mechanisms that control the interdependencies. This paper presents a framework for the definition of interdependencies that frequently occur in collaborative activities. By means of a clear characterization of interdependencies, it is possible to identib coordination mechanisms to manage them, opening the way toward a power@ coordination tool capable of encompassing a wide range of collaborative applications. An implementation of the coordination model of a collaborative virtual environment based on the proposed framework is given as example.
This article presents an approach for generating steering behaviors of groups of characters based on the space colonization algorithm that has been used in the past for generating leaf venation patterns and tree structures. In this article, the underlying idea of the space colonization algorithm is adapted to control the motion of virtual characters, providing robust and realistic group behaviors by adjusting just a few parameters. The main contributions of this work are the robustness, flexibility, and simplicity of the proposed approach to control groups of characters in an interactive way, providing path planning and a series of group behaviors, such as group formation, alignment among others. We also introduce a possible extension of this model to provide collision avoidance among agents, mainly focused on crowd simulation. In addition, an interactive tool is provided to allow an easy manner for controlling the motion of virtual characters.
Abstract. The use of remote sensing images as a source of information in agribusiness applications is very common. In those applications, it is fundamental to know how the space occupation is. However, identification and recognition of crop regions in remote sensing images are not trivial tasks yet. Although there are automatic methods proposed to that, users very often prefer to identify regions manually. That happens because these methods are usually developed to solve specific problems, or, when they are of general purpose, they do not yield satisfying results. This work presents a new interactive approach based on relevance feedback to recognize regions of remote sensing. Relevance feedback is a technique used in content-based image retrieval (CBIR) tasks. Its objective is to aggregate user preferences to the search process. The proposed solution combines the Optimum-Path Forest (OPF) classifier with composite descriptors obtained by a Genetic Programming (GP) framework. The new approach has presented good results with respect to the identification of pasture and coffee crops, overcoming the results obtained by a recently proposed method and the traditional Maximimun Likelihood algorithm.
This paper deals with the behavior of virtual environments from the collaboration point-of-view, in which actors (human or virtual beings) interact and collaborate by means of interdependent tasks. In this sense, actors may realize tasks that are dependent on tasks performed by other actors, while the interdependencies between tasks (through resource management and temporal relations) delineate the overall behavior of a virtual environment. Our main goal is to propose an approach for the coordination of those behaviors. Initially a generic study of possible interdependencies between collaborative tasks is presented, followed by the formal modeling (using Petri Nets) of coordination mechanisms for those dependencies. In order to implement such mechanisms, an architecture of reusable and pluggable coordination components is also introduced. These components are used in an implementation of a multi-user videogame. The presented approach is a concrete step to create virtual societies of actors that collaborate to reach common goals without the risk of getting involved in conflicting or repetitive tasks. r
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