A critical challenge to creating effective agent-based systems is allowing them to operate effectively when the operating environment is complex, dynamic, and error-prone. In this...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
The interaction of an autonomous mobile robot with the real world critically depends on the robots morphology and on its environment. Building a model of these aspects is extremel...
We propose a scheme for indoor place identication based on the recognition of global scene
views. Scene views are encoded using a holistic representation that provides low-resolu...
— In mobile robotics, the segmentation of range data is an important prerequisite to object recognition and environment understanding. This paper presents an algorithm for realti...