We present a learning approach for efficiently inducing adaptive behaviour of route
instructions. For such a purpose we propose a two-stage approach to learn a hierarchy of …

Patterns of qualitative concepts are extracted from robot sensors in order to describe the
shapes, colours, spatial orientations and topology situations of natural landmarks in the …

Typically, autonomous robot navigation relies on a detailed, accurate map. The associated
representations, however, do not readily support human-friendly interaction. The approach …

Reinforcement learning has developed as a successful learning approach for domains that
are not fully understood and that are too complex to be described in closed form. However …

This paper describes how a cognitive architecture builds a spatial model and navigates from
it without a map. Each constructed model is a collage of spatial affordances that describes …

Geographic question answering (QA) systems can be used to help make geographic
knowledge accessible by directly giving answers to natural language questions. In this …

A safe (ie collision-free) and efficient movement of a mobile autonomous system requires a
correct assessment of the vehiclesʼ environment. In many systems, the spatial context is …

Sketch maps are an intuitive way of expressing geospatial information. They contain objects
which represent real world geographic features, relations between these objects, and …

In this chapter, we take a deeper look into the nature of abstraction. In particular, this chapter
argues for the use of state space abstraction (Sect. 4.1) and presents a formal framework of …

This chapter contains an empirical evaluation of the learning performance and
generalization and transfer learning capabilities of RLPR-based representations in a goal …