Abstract
Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players' strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. © 2011 IEEE.

Abstract
The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players' strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players' models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition. © 2011 Springer-Verlag.

Abstract
Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players' strategies to negotiate in the market. The proposed methodology is multi-agent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.

Abstract
This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition. In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in.

Abstract
Nowadays, there is a wide range of commercial LBMS (Location-Based Mobile Services) available in the market, and a trend towards the display of 3D maps can be clearly observed. Given the complete disparity of ideas and a visible commercial orientation in the industry, the study of the visualization aspects that influence user performance and experience in the exploration of urban environments, using 3D maps, becomes an important issue. Based on a proposed conceptual framework, an online questionnaire was developed and administered in order to measure the real impact of each element. Combining the experimental results with the current state-of-the-art, a new visualization paradigm is defined in a dual specification: "layers" providing relevant visual content to the map, and "functions" providing the necessary functionality.

Abstract
We describe a real-time facade tracking system that uses, as setup information, only two images of a facade, captured on the moment. No more previous information is needed, such as a facade 3D model, dimensions or aspect ratio. Feature points and their local descriptors are extracted from that pair of images and used during the detection and tracking of the facade. Additionally, parallax and topological information is also used in order to increase the overall robustness of the tracking process. Experiments show that the system can detect and track a wide variety of facades, including those that are not entirely planar, partially occluded or have few distinguishable visual landmarks. The reliance on on-the-spot information, alone, makes this system useful for Outdoor Augmented Reality applications, in an Anywhere Augmentation urban context.