Orientador: Jônatas Manzolli / Acompanhado de 1 DVD / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Artes / Made available in DSpace on 2018-08-16T00:39:52Z (GMT). No. of bitstreams: 1 Furlanete_FabioParra_D.pdf: 3804356 bytes, checksum: 366c9164940cf5018b191cc60707d3d8 (MD5) Previous issue date: 2010 / Resumo: Este trabalho investiga o possível papel para o compositor em uma situação de interação musical coletiva e propõe estrategias para sua atuação nesse contexto. Apresenta exemplos dessas estrategias em trabalhos composicionais e implementa um desses trabalhos na forma de uma ferramenta digital que permite ao compositor modelar contextos interativos, elaborar regras de interação e interferir nos processos enquanto eles ocorrem. A implementação das ferramentas digitais é feita na forma de um sistema para modelagem sonora coletiva que usa o projeto de jogos digitais como modelo para interação musical entre agentes artificiais e jogadores humanos em rede. Nosso trabalho tem como foco as regras de interação e como elas podem ser projetadas gerar resultados esteticamente atraentes e que ao mesmo tempo não restrinjam excessivamente a autonomia criativa dos jogadores. Essas regras devem ser aplicáveis tanto no contexto da Arte-Educação quanto no da performance. Acreditamos que o conhecimento da área de design de jogos em rede é útil para o projeto de tais regras. / Abstract: This work investigates the possible role for the composer in a situation of collective musical interaction and proposes strategies for their action in this context. It presents examples of these strategies in compositional works and implements them in the form of computer tools that allows the composer to model interactive contexts, develop rules of interaction and interfere with the processes as they occur. The implementation of the computer tools is in the form of a system for collective sound shaping. It uses digital games design patterns as models for musical interaction between artificial agents and human players in a network. Our work aimed to the interaction rules and how they can be designed to provide interactions whose outcome is aesthetically appealing and, at the same time, to not restrict the creative autonomy of the players. These rules should be applicable both in the context of Art Education and in the performance. We believe that knowledge of the project area network gaming is useful for the design of such rules. / Doutorado / Doutor em Música

A characteristic challenge of software development is the management of omnipresent change. Classically, this constant change is driven by customers changing their requirements. The wish to optimally leverage available resources opens another source of change: the software systems environment. Software is tailored to specific platforms (e.g., hardware architectures) resulting in many variants of the same software optimized for different environments. If the environment changes, a different variant is to be used, i.e., the system has to reconfigure to the variant optimized for the arisen situation. The automation of such adjustments is subject to the research community of self-adaptive systems. The basic principle is a control loop, as known from control theory. The system (and environment) is continuously monitored, the collected data is analyzed and decisions for or against a reconfiguration are computed and realized. Central problems in this field, which are addressed in this thesis, are the management of interdependencies between non-functional properties of the system, the handling of multiple criteria subject to decision making and the scalability. In this thesis, a novel approach to self-adaptive software--Multi-Quality Auto-Tuning (MQuAT)--is presented, which provides design and operation principles for software systems which automatically provide the best possible utility to the user while producing the least possible cost. For this purpose, a component model has been developed, enabling the software developer to design and implement self-optimizing software systems in a model-driven way. This component model allows for the specification of the structure as well as the behavior of the system and is capable of covering the runtime state of the system. The notion of quality contracts is utilized to cover the non-functional behavior and, especially, the dependencies between non-functional properties of the system. At runtime the component model covers the runtime state of the system. This runtime model is used in combination with the contracts to generate optimization problems in different formalisms (Integer Linear Programming (ILP), Pseudo-Boolean Optimization (PBO), Ant Colony Optimization (ACO) and Multi-Objective Integer Linear Programming (MOILP)). Standard solvers are applied to derive solutions to these problems, which represent reconfiguration decisions, if the identified configuration differs from the current. Each approach is empirically evaluated in terms of its scalability showing the feasibility of all approaches, except for ACO, the superiority of ILP over PBO and the limits of all approaches: 100 component types for ILP, 30 for PBO, 10 for ACO and 30 for 2-objective MOILP. In presence of more than two objective functions the MOILP approach is shown to be infeasible.

A characteristic challenge of software development is the management of omnipresent change. Classically, this constant change is driven by customers changing their requirements. The wish to optimally leverage available resources opens another source of change: the software systems environment. Software is tailored to specific platforms (e.g., hardware architectures) resulting in many variants of the same software optimized for different environments. If the environment changes, a different variant is to be used, i.e., the system has to reconfigure to the variant optimized for the arisen situation. The automation of such adjustments is subject to the research community of self-adaptive systems. The basic principle is a control loop, as known from control theory. The system (and environment) is continuously monitored, the collected data is analyzed and decisions for or against a reconfiguration are computed and realized. Central problems in this field, which are addressed in this thesis, are the management of interdependencies between non-functional properties of the system, the handling of multiple criteria subject to decision making and the scalability. In this thesis, a novel approach to self-adaptive software--Multi-Quality Auto-Tuning (MQuAT)--is presented, which provides design and operation principles for software systems which automatically provide the best possible utility to the user while producing the least possible cost. For this purpose, a component model has been developed, enabling the software developer to design and implement self-optimizing software systems in a model-driven way. This component model allows for the specification of the structure as well as the behavior of the system and is capable of covering the runtime state of the system. The notion of quality contracts is utilized to cover the non-functional behavior and, especially, the dependencies between non-functional properties of the system. At runtime the component model covers the runtime state of the system. This runtime model is used in combination with the contracts to generate optimization problems in different formalisms (Integer Linear Programming (ILP), Pseudo-Boolean Optimization (PBO), Ant Colony Optimization (ACO) and Multi-Objective Integer Linear Programming (MOILP)). Standard solvers are applied to derive solutions to these problems, which represent reconfiguration decisions, if the identified configuration differs from the current. Each approach is empirically evaluated in terms of its scalability showing the feasibility of all approaches, except for ACO, the superiority of ILP over PBO and the limits of all approaches: 100 component types for ILP, 30 for PBO, 10 for ACO and 30 for 2-objective MOILP. In presence of more than two objective functions the MOILP approach is shown to be infeasible.