SPIDA: Abstracting and generalizing layout design cases

Abstraction and generalization of layout design cases generate new knowledge that is more widely applicable to use than specific design cases. The abstraction and generalization of design cases into hierarchical levels of abstractions provide the designer with the flexibility to apply any level of abstract and generalized knowledge for a new layout design problem. Existing case-based layout learning (CBLL) systems abstract and generalize cases into single levels of abstractions, but not into a hierarchy. In this paper, we propose a new approach, termed customized viewpoint - spatial (CV-S), which supports the generalization and abstraction of spatial layouts into hierarchies along with a supporting system, SPIDA (SPatial Intelligent Design Assistant)

Waltz User Manual

This Document describes relevant information to understand and control the Waltz Visualization System. Waltz is a tool to visualize three dimensional data and reads special reference files containing details of the data file, path name, dimensions and aspect ratios of the data. Waltz (as the name suggests) contains three parts: Generalization, Specialization and Abstraction. The Generalization Process splits the data into spatially connected groups. A specialization is formed from a subset (selection) of these groups. The results are displayed in multiple abstract views of the same data. These abstractions are formed by losing or augmenting the data to facilitate in the understanding of the data

Mathematical Abstraction, Conceptual Variation and Identity

One of the key features of modern mathematics is the adoption of the abstract method. Our goal in this paper is to propose an explication of that method that is rooted in the history of the subject

On Object-Orientation

Although object-orientation has been around for several decades, its key concept abstraction has not been exploited for proper application of object-orientation in other phases of software development than the implementation phase. We mention some issues that lead to a lot of confusion and obscurity with object-orientation and its application in software development. We describe object-orientation as abstract as possible such that it can be applied to all phases of software development

Hi-Val: Iterative Learning of Hierarchical Value Functions for Policy Generation

Task decomposition is effective in manifold applications where the global complexity of a problem makes planning and decision-making too demanding. This is true, for example, in high-dimensional robotics domains, where (1) unpredictabilities and modeling limitations typically prevent the manual specification of robust behaviors, and (2) learning an action policy is challenging due to the curse of dimensionality. In this work, we borrow the concept of Hierarchical Task Networks (HTNs) to decompose the learning procedure, and we exploit Upper Confidence Tree (UCT) search to introduce HOP, a novel iterative algorithm for hierarchical optimistic planning with learned value functions. To obtain better generalization and generate policies, HOP simultaneously learns and uses action values. These are used to formalize constraints within the search space and to reduce the dimensionality of the problem. We evaluate our algorithm both on a fetching task using a simulated 7-DOF KUKA light weight arm and, on a pick and delivery task with a Pioneer robot