One problem of the current network programming implementation in TinyOS 1.1 is that it takes much longer than the tranditional in-sytem-programming due to the slow radio connection. We extended the implementation so that it uses the history of the previous version to reduce the transmission time. For a small amount of change in the source code, we achieved around 3.5 times of the speed-up. And ...

Let X be a finite set of v elements, called points, and let β be a finite family of distinct k-subsets of X , called blocks. Then the pair D = (X ,β) is called a t-design with parameters (v,k,λ) if any t-subset of X is contained in exactly λ members of β. If λi denotes the number of blocks containing i points, i = 0,1,2, . . . , t−1, then λi is independent of the choice of the i points and λi (...

Since most current scene understanding approaches operate either on the 2D image or using a surface-based representation, they do not allow reasoning about the physical constraints within the 3D scene. Inspired by the “Blocks World” work in the 1960’s, we present a qualitative physical representation of an outdoor scene where objects have volume and mass, and relationships describe 3D structure...

In this paper, we describe an improvement on the task of giving instructions to robots in a simulated block world using unrestricted natural language commands.

Standard tours combined with lack of information make many tourists miss some important experiences a destination has to offer. The target of the Dynamic Tour Guide (DTG) is to discover Tour Building Blocks (TBB), e.g. attractions like sights or restaurants, dependent on the actual context which is defined by personal interests, location and schedule of a tourist. It determines current informat...

In this paper we are concerned with the problem of learning how to solve planning problems in one domain given a number of solved instances. This problem is formulated as the problem of inferring a function that operates over all instances in the domain and maps states and goals into actions. We call such functions generalized policies and the question that we address is how to learn suitable r...