We introduce a memory model for robots that can account for many aspects of an inner
world, ranging from object permanence, episodic memory, and planning to imagination and …

An adaptive perception system enables humanoid robots to interact with humans and their
surroundings in a meaningful context-dependent manner. An important foundation for visual …

We describe how a standard reinforcement learning algorithm can be changed to include a
second contextual input that is used to modulate the learning in the original algorithm. The …

We present research in synthetic social behavior for interactive virtual characters. We
describe a model from the natural world, the gray wolf (Canis lupus), and the social behavior …

A computational model with three interacting components for context sensitive reinforcement
learning, context processing and automation can autonomously learn a focus attention and …

Emotion is an important aspect of human intelligence and has been shown to play a
significant role in the human decision-making process. This paper proposes a …

The core deficit in attention deficit/hyperactivity disorder (ADHD) continues to present an
enigma to scientists, professionals and parents alike. Medication with methylphenidate has …

We present a new robotic implementation of a brain-inspired model of action selection
described by Gurney et al.(Gurney et al., 2001a, Gurney et al., 2001b) based on neural …

Ikaros is an open framework for system-level brain modeling and real-time robot control.
Version 2 of the system includes a range of computational components that implements …

For future network scenarios to exhibit autonomic behaviour, both networks and application
components and services need to be aware of their computational and environmental …