Showing papers on "Applications of artificial intelligence published in 1970"

Artificial Intelligence In Engineering:Past, Present And Future

Abstract: This is a review paper which sets the scene by defining some fundamental concept, such as intelligence and intelligent systems, and then discusses current trends in applications of artificial intelligence in engineering. The author reviews five key paradigms of artificial intelligence in engineering: knowledge-based systems, neural networks, genetic algorithms, fuzzy logic and intelligent agents.

Choosing between different AI approaches? The scientific benefits of the confrontation, and the new collaborative era between humans and machines

Abstract: AI is a multidisciplinary activity that involves specialists from several fields, and we can say that the aim of science, and AI science, is solving problems. AI and computer sciences are been creating a new kind of making science, that we can call in silico science. Both models top-eown and bottomup are useful for e-scientific research. There is no a real controversy between them. Besides, the extended mind model of human cognition, involves human-machine interactions. Huge amount of data requires new ways to make and organize scientific practices: supercomputers, grids, distributed computing, specific software and middleware and, basically, more efficient and visual ways to interact with information. This is one of the key points to understand contemporary relationships between humans and machines: usability of scientific data.

Approaching artificial intelligence for games - the Turing Test revisited

Abstract: Today's powerful computers have increasingly more resources available, which can be used for incorporating more sophisticated AI into home applications like computer games. The perhaps obvious way of using AI to enhance the experience of a game is to make the player perceive the computer-controlled entities as intelligent. The traditional idea of how to determine whether a machine can pass as intelligent is the Turing Test. In this paper we show that it is possible and useful to conduct a test adhering to the intention of the original Turing test. We present an empirical study exploring human discrimination of artificial intelligence from the behaviour of a computer-controlled entity used in its specific context and how the behaviour responds to the user's expectations. In our empirical study the context is a real-time strategy computer game and the purpose of the AI is merely to pass as an acceptable opponent. We discuss the results of the empirical study and its implications for AI in computer applications.

The Role Of Perception And Action In Intelligent Systems

Abstract: Robotics plays an important role in the applications of Artificial Intelligence in Engineering, since it deals with the interaction of an intelligent system with the world by means of perception and action. However, Robotics has been traditionaly considered as just a mere application area of AI. In this paper, the role of perception and action in current AI systems is analyzed and some recent fundamental results concerning the use of Robotic Intelligence for applications of AI in Engineering are discussed, in order to build artificial systems that behave in an intelligent way in the real world. Finally, two implemented systems based on this methodology are described to show the relevance of the proposed strategy to Engineering applications, one using visual perception, and another based on force/torque sensing.

Technical Criteria For Selecting Expert System ShellsFor Engineering Applications

Abstract: A large number of Artificial Intelligence applications in engineering are based on the use of expert systems. One of the fundamental decisions that should be made initially is the selection of the most appropriate development shell. The most frequent types of engineering applications has evolved over the last few years in such a way that it is no longer possible to think of a single large isolated expert system running on a mainframe or minicomputer; instead, we must now consider an embedded subsystem subject to new requirements. The existence of more than a hundred commercial shells currently available on the market makes the problem even more complicated. The bases for an initial evaluation and selection of these shells for the most frequent type of engineering problems are presented in this paper. It is intended that the different aspects involved in the problem will be clarified. To achieve this, a systematic and rigorous process based on an empirical methodology for expert system shells evaluation and selection has been followed. In the paper, a general framework for the problem is first presented and then the identification of the capabilities and characteristics of the required shell are described: user aspects, technical aspects, cost and vendor. Next, the requirements imposed by the application type are discussed: eight application types are distinguished, the requirements for reasoning mode and the problem of fact-base unfeasibility are dealt with. The question of rapid prototype development is also analyzed. Some capacities that are critical for the success of the project are identified, such as the support for personal computers, embeddability, backward chaining, connection to databases, etc. Following the established criteria, details of 31 common shells are finally included.