Authors: Ankush Narkhede and Asutosh Kumar Pandey
Department of Computer Science, Oriental University, Indore
Department of Engineering Chemistry Rishiraj Institute of Technology, Indore
In this paper, we outline our approach to incrementally building complete intelligent creatures. The fundamental decomposition of the intelligent system is not into independent information processing units, which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity producers, which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporate everything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots, which operate without supervision as creatures in standard office environments.
Artificial intelligence started as a field whose goal was to replicate human level intelligence in a machine. Early hopes diminished as the magnitude and difficulty of that goal was appreciated. Slow progress was made over the next 25 years in demonstrating isolated aspects of intelligence. Recent work has tended to concentrate on commercializable aspects of “intelligent assistants” for human workers. No one talks about replicating the full gamut of human intelligence any more. Instead, we see a retreat into specialized sub problems, such as ways to represent knowledge, natural language understanding, vision or even more specialized areas such as truth maintenance systems or plan verification. All the work in these subareas is benchmarked against the sorts of tasks humans do within those areas. Amongst the dreamers still in the field of AI , there is a feeling. That one day all these pieces will all fall into place and we will see “truly” intelligent systems emerge. However, I, and others, believe that human level intelligence is too complex and little understood to be correctly decomposed into the right sub pieces at the moment and that even if we knew the sub pieces we still wouldn’t know the right interfaces between them. Furthermore, we will never understand how to decompose human level intelligence until we’ve had a lot of practice with simpler level intelligences. In this paper, the argue for a different approach to creating artificial intelligence:
We must incrementally build up the capabilities of intelligent systems, having complete systems at each step of the way and thus automatically ensure that the pieces and their interfaces are valid.
At each step, we should build complete intelligent systems that we let loose in the real world with real sensing and real action. Anything less provides a candidate with which we can delude ourselves. We have been following this approach and have built a series of autonomous mobile robots. We have reached an unexpected conclusion (C) and have a rather radical hypothesis (H).When we examine very simple level intelligence we find that explicit representations and models of the world simply get in the way. It turns out to be better to use the world as its own model. (H) Representation is the wrong unit of abstraction in building the bulkiest parts of intelligent systems. Representation has been the central issue in artificial intelligence work over the last 15 years only because it has provided an interface between otherwise isolated modules and conference papers.