Abstract: The discipline of Artificial Intelligence (AI) was born in the summer of 1956 at Dartmouth College in Hanover, New Hampshire. Half of a century has passed, and AI has turned into an important field whose influence on our daily lives can hardly be overestimated. The original view of intelligence as a computer program – a set of algorithms to process symbols – has led to many useful applications now found in internet search engines, voice recognition software, cars, home appliances, and consumer electronics, but it has not yet contributed significantly to our understanding of natural forms of intelligence. Since the 1980s, AI has expanded into a broader study of the interaction between the body, brain, and environment, and how intelligence emerges from such interaction. This advent of embodiment has provided an entirely new way of thinking that goes well beyond artificial intelligence proper, to include the study of intelligent action in agents other than organisms or robots. For example, it supplies powerful metaphors for viewing corporations, groups of agents, and networked embedded devices as intelligent and adaptive systems acting in highly uncertain and unpredictable environments. In addition to giving us a novel outlook on information technology in general, this broader view of AI also offers unexpected perspectives into how to think about ourselves and the world around us. In this chapter, we briefly review the turbulent history of AI research, point to some of its current trends, and to challenges that the AI of the 21st century will have to face.
Abstract: New Robotics designates an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e.g. from control theory), designing agents in the New Robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics or design principles, that on the one hand capture theoretical insights about intelligent – adaptive – behavior, and on the other provide guidance in actually designing and building systems. In this paper we provide an overview of all the principles but focus on the principles of 'ecological balance' which concerns the relation between environment, morphology, materials, and control, and 'sensory-motor coordination' which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we will argue, artificial evolution together with morphogenesis is not only 'nice to have' but is in fact a necessary tool for designing embodied agents.
Abstract: This paper details an iterative, rapid method for digital mock-up and the evolutionary optimisation of a closed loop controller for highly dynamic gaits. The evolutionary approach in the virtual construction kit MorphEngine is investigated on its capacity to inspire and evolve behaviours for legged robots and non-biometric locomotion. The tool supports the engineer in finding, controlling and finally implementing gaits based on emergent dynamics on a real-world robot through the iterative exploitation of both the agents morphology and its physical environment.