The visual interpretation of data is an essential step to guide any further processing or decision making. Dimensionality reduction (or manifold learning) tools may be used for visualization if the resulting dimension is constrained to be 2 or 3. The field of machine learning has developed numerous nonlinear dimensionality reduction tools in the last decades. However, the diversity of methods r...

This paper defines the agile enterprise as one which is able to both manage and apply knowledge effectively, and suggests that value from either capability is impeded if they are not in balance. It looks at the application of knowledge as requiring a change, and overviews a body of analytical work on change proficiency in business systems and processes. It looks at knowledge management as a str...

Recent research indicates that practicing on a joint spatial compatibility task with an incompatible stimulus-response mapping affects subsequent joint Simon task performance, eliminating the social Simon effect. It has been well established that in individual contexts, for transfer of learning to occur, participants need to practice an incompatible association between stimulus and response pos...

The future of robots, as our companions is dependent on their ability to understand, interpret and represent the environment in a human compatible manner. Towards this aim, the presented work is part of an attempt to create a hierarchical probabilistic concept-oriented representation of space, based on objects. Specifically, this work details efforts taken towards learning and generating concep...