Search

Multiobjective search is a generalization of the Shortest Path Problem where several (usually conflicting) criteria are optimized simultaneously. The paper presents an extension of the single-objective IDA* search algorithm to the multiobjective case. The new algorithm is illustrated with an example, and formal proofs are presented on its termination, completeness, and admissibility. The algorithm is evaluated over a set of random tree search problems, and is found to be more efficient than IDMOA*, a previous extension of IDA* to the multiobjective case. [ABSTRACT FROM AUTHOR]

The paper develops vector frontier search, a new multiobjective search strategy that achieves an important reduction in space requirements over previous proposals. The complexity of a resulting multiobjective frontier search algorithm is analyzed and its performance is evaluated over a set of random problems. [ABSTRACT FROM AUTHOR]

This paper describes a novel stereovision matching approach based on omni-directional images obtained with fish-eye lenses in forest environments. The goal is to obtain a disparity map as a previous step for determining the volume of wood in the imaged area. The interest is focused on the trunks of the trees. Due to the irregular distribution of the trunks, the most suitable features are the pixels. A set of six attributes is used for establishing the matching between the pixels in both images of each stereo pair analysed. The final decision about the matched pixels is taken based on a well tested Fuzzy Multi-Criteria Decision Making approach, where the attributes determine the criteria and the potential matches in one image of the stereo pair for a given pixel in the other one determine the alternatives. The application of this decision making approach makes the main finding of the paper. The full procedure is based on the application of three well known matching constraints. The proposed approach is compared favourably against the usage of simple features. [ABSTRACT FROM AUTHOR]

P2P file sharing systems are distributed systems consisting of interconnected nodes able to organize themselves in networks, with the purpose of sharing content. Recent empirical studies have shown that they suffer from freeloaders, that is, peers that consume many more resources or content than they contribute. In this paper we propose a coalition formation based incentive mechanism for P2P file sharing systems, that improves the system performance for the coalition participant peers. In addition, it discourages free-loader like behavior. The mechanism presents a formal approach to the problem based on game theory that takes into account the rational and self-interested behavior of the peers. [ABSTRACT FROM AUTHOR]