Transmission cost allocation using cooperative game theory: a comparative study

In this paper is presented a Game Theory based methodology to allocate transmission costs, considering cooperation and competition between producers. As original contribution, it finds the degree of participation on the additional costs according to the demand behavior. A comparative study was carried out between the obtained results using Nucleolus balance and Shapley Value, with other techniques such as Averages Allocation method and the Generalized Generation Distribution Factors method (GGDF). As example, a six nodes network was used for the simulations. The results demonstrate the ability to find adequate solutions on open access environment to the networks.

TimeMesh: an educational historical game

The TIMEMESH game, developed in the scope of the European Project SELEAG, is an educational game for learning history, culture and social relations. It is supported by an extensible, online, multi-language, multi-player, collaborative and social platform for sharing and acquiring knowledge of the history of European regions. The game has been already used, with remarkable success, in different European countries like Portugal, Spain, England, Slovenia, Estonia and Belgium.

Coordinated runtime adaptations in cooperative open real-time systems

This paper proposes an one-step decentralised coordination model based on an effective feedback mechanism to reduce the complexity of the needed interactions among interdependent nodes of a cooperative distributed system until a collective adaptation behaviour is determined. Positive feedback is used to reinforce the selection of the new desired global service solution, while negative feedback discourages nodes to act in a greedy fashion as this adversely impacts on the provided service levels at neighbouring nodes. The reduced complexity and overhead of the proposed decentralised coordination model are validated through extensive evaluations.

Time-bounded distributed QoS-aware service configuration in heterogeneous cooperative environments

The scarcity and diversity of resources among the devices of heterogeneous computing environments may affect their ability to perform services with specific Quality of Service constraints, particularly in dynamic distributed environments where the characteristics of the computational load cannot always be predicted in advance. Our work addresses this problem by allowing resource constrained devices to cooperate with more powerful neighbour nodes, opportunistically taking advantage of global distributed resources and processing power. Rather than assuming that the dynamic configuration of this cooperative service executes until it computes its optimal output, the paper proposes an anytime approach that has the ability to tradeoff deliberation time for the quality of the solution. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves at each iteration, with an overhead that can be considered negligible.

Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Decentralized Target Tracking based on Multi-Robot Cooperative Triangulation

Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.

Formation Control Driven by Cooperative Object Tracking

In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.

Coalition of distributed generation units to Virtual Power Players - a game theory approach

Smart Grids (SGs) have emerged as the new paradigm for power system operation and management, being designed to include large amounts of distributed energy resources. This new paradigm requires new Energy Resource Management (ERM) methodologies considering different operation strategies and the existence of new management players such as several types of aggregators. This paper proposes a methodology to facilitate the coalition between distributed generation units originating Virtual Power Players (VPP) considering a game theory approach. The proposed approach consists in the analysis of the classifications that were attributed by each VPP to the distributed generation units, as well as in the analysis of the previous established contracts by each player. The proposed classification model is based in fourteen parameters including technical, economical and behavioural ones. Depending of the VPP strategies, size and goals, each parameter has different importance. VPP can also manage other type of energy resources, like storage units, electric vehicles, demand response programs or even parts of the MV and LV distribution network. A case study with twelve VPPs with different characteristics and one hundred and fifty real distributed generation units is included in the paper.

A framework for real time MMO game content generation

Com o aumento de plataformas móveis disponíveis no mercado e com o constante incremento na sua capacidade computacional, a possibilidade de executar aplicações e em especial jogos com elevados requisitos de desempenho aumentou consideravelmente. O mercado dos videojogos tem assim um cada vez maior número de potenciais clientes. Em especial, o mercado de jogos massive multiplayer online (MMO) tem-se tornado muito atractivo para as empresas de desenvolvimento de jogos. Estes jogos suportam uma elevada quantidade de jogadores em simultâneo que podem estar a executar o jogo em diferentes plataformas e distribuídos por um "mundo" de jogo extenso. Para incentivar a exploração desse "mundo", distribuem-se de forma inteligente pontos de interesse que podem ser explorados pelo jogador. Esta abordagem leva a um esforço substancial no planeamento e construção desses mundos, gastando tempo e recursos durante a fase de desenvolvimento. Isto representa um problema para as empresas de desenvolvimento de jogos, e em alguns casos, e impraticável suportar tais custos para equipas indie. Nesta tese e apresentada uma abordagem para a criação de mundos para jogos MMO. Estudam-se vários jogos MMO que são casos de sucesso de modo a identificar propriedades comuns nos seus mundos. O objectivo e criar uma framework flexível capaz de gerar mundos com estruturas que respeitam conjuntos de regras definidas por game designers. Para que seja possível usar a abordagem aqui apresentada em v arias aplicações diferentes, foram desenvolvidos dois módulos principais. O primeiro, chamado rule-based-map-generator, contem a lógica e operações necessárias para a criação de mundos. O segundo, chamado blocker, e um wrapper à volta do módulo rule-based-map-generator que gere as comunicações entre servidor e clientes. De uma forma resumida, o objectivo geral e disponibilizar uma framework para facilitar a geração de mundos para jogos MMO, o que normalmente e um processo bastante demorado e aumenta significativamente o custo de produção, através de uma abordagem semi-automática combinando os benefícios de procedural content generation (PCG) com conteúdo gráfico gerado manualmente.