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By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering with Gaussians only, (2) Gaussian mixture filtering for strong nonlinearities, (3) Gaussian process filtering for purely data-driven scenarios. For each setting, efficient algorithms are derived and applied to real-world problems.
This book explores the roles of national actors within international organizations, with particular emphasis on the collaborative approach adopted by Nordic governments and associations. Analyzing Nordic regional cooperation within international organizations, this volume seeks to shed light on the politics of alignment and distinct macro-regional identity-building in international arenas. Exploring the middle ground between the national and the international, contributors discuss how Nordic governments and associations have successfully created and used the image of a distinct group within the international system and where they have failed. Presenting a richer picture of international and ...
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This book provides a scientific forecast of development in aquaculture with a focus on the environmental, technological, social and economic constraints that need to be resolved to ensure sustainable development of the industry and allow the industry to be able to feed healthy seafood products to future generations. The chapters discuss the most critical bottlenecks of the development. They encompass subjects of understanding the environmental impacts, the current state-of-the-art in monitoring programs and in coastal zone management, the important interactions between wild and cultured organisms including release of non-native species into the wild.
The Eighth Scandinavian Conference on Artificial Intelligence continues a tradition of being one of the most important regional AI conferences in Europe. Keith Downing focuses on the low road to artificial intelligence, that is, the development of AI through evolutionary artificial life approaches. The topics of the accepted papers range from multi-agent systems, robots, natural languages and machine learning to general knowledge-based systems and formal approaches to AI. This collection of papers together exemplifies the diversity of research in artificial intelligence today. Two of the invited speakers, both focus on vision, although each from slightly different viewpoints. One considers biological models for vision and its consequences for artificial vision, whereas the other considers the relation between real world objects and their internal representation in robots. The last keynote speaker, presents answer set programming, a new idea for declarative programming.