Abstract
This paper presents an overview of the RoboCup Rescue Simulation League and the rescue team FC Portugal. RoboCup Rescue Simulation is an international joint project that promotes research on distributed artificial intelligence and intelligent robotics. It offers a comprehensive urban disaster simulator and a competitive evaluation for researchers. This paper explains the objectives of the league, the mechanics of the simulator system and the main challenges in the research conducted using the RoboCup Rescue simulator. In this ever evolving and extensive urban disaster simulator, heterogeneous teams of agents try to minimize damage to both people and urban property after the occurrence of an earthquake. The city is filled with burning buildings, civilians trapped under debris and blocked roads. Teams of simulated fire brigades, policeman and ambulances collaborate in order to face the disaster. In this context, an overview of FC Portugal's rescue team is presented, including the major coordination algorithms and implemented agent's behaviours. Some of the most interesting league problems are discussed and FC Portugal's solutions are introduced. Results achieved in international competitions are also briefly presented, with emphasis on the last European championship, held in 2006, in Eindhoven, which FC Portugal won.

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The Visual Object Information Retrieval (VOIR) system described in this paper implements an image retrieval approach that combines two layers, the conceptual and the visual layer. It uses terms from a textual thesaurus to represent the conceptual information and also works with image regions, the visual information. The terms are related with the image regions through a weighted association enabling the execution of concept-level queries. VOIR uses region-based relevance feedback to improve the quality of the results in each query session and to discover new associations between text and image. This paper describes a user-centred and task-oriented comparative evaluation of VOIR which was undertaken considering three distinct versions of VOIR: a full-fledge version; one supporting relevance feedback only at image level; and a third version not supporting relevance feedback at all. The evaluation performed showed the usefulness of region based relevance feedback in the context of VOIR prototype.

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