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AISB91 is the eighth conference organized by the Society for the Study of Artificial Intelligence and Simulation of Behaviour. It is not only the oldest regular conference in Europe on AI - which spawned the ECAI conferences in 1982 - but it is also the conference that has a tradition for focusing on research as opposed to applications. The 1991 edition of the conference was no different in this respect. On the contrary, research, and particularly newly emerging research dir ections such as knowledge level expert systems research, neural networks and emergent functionality in autonomous agents, was strongly emphasised. The conference was organized around the following sessions: dis tributed intelligent agents, situatedness and emergence in autonomous agents, new modes of reasoning, the knowledge level perspective, and theorem proving and machine learning. Each of these sessions is discussed below in more detail. DISTRIBUTED INTELLIGENT AGENTS Research in distributed AI is concerned with the problem of how multiple agents and societies of agents can be organized to co-operate and collectively solve a problem. The first paper by Chakravarty (MIT) focuses on the problem of evolving agents in the context of Minsky's society of mind theory. It addesses the question of how new agents can be formed by transforming existing ones and illustrates the theory with an example from game playing. Smieja (GMD, Germany) focuses on the problem of organizing networks of agents which consist internally of neural networks.
Second Generation Expert Systems have been a very active field of research during the last years. Much work has been carried out to overcome drawbacks of first generation expert systems. This book presents an overview and new contributions from people who have played a major role in this evolution. It is divided in several sections that cover the main topics of the subject: - Combining Multiple Reasoning Paradigms - Knowledge Level Modelling - Knowledge Acquisition in Second Generation Expert Systems - Explanation of Reasoning - Architectures for Second Generation Expert Systems. This book can serve as a reference book for researchers and students and will also be an invaluable help for practitioners involved in KBS developments.
Dealing with the theme of prospects for artificial inteligence as the general science of intelligence, this work covers a wide range of topics. It attempts to identify trends and projects into the future, instead of simply surveying past achievements.
The re-use of abstract models of problem solving is a major step towards cost-effective and quality-assured knowledge-based system development. The techniques are discussed in this text.
"This book introduces and explains Higher Order Neural Networks (HONNs) to people working in the fields of computer science and computer engineering, and how to use HONNS in these areas"--Provided by publisher.
Researchers in Artificial Intelligence have traditionally been classified into two categories: the “neaties” and the “scruffies”. According to the scruffies, the neaties concentrate on building elegant formal frameworks, whose properties are beautifully expressed by means of definitions, lemmas, and theorems, but which are of little or no use when tackling real-world problems. The scruffies are described (by the neaties) as those researchers who build superficially impressive systems that may perform extremely well on one particular case study, but whose properties and underlying theories are hidden in their implementation, if they exist at all. As a life-long, non-card-carrying scruffy, I was naturally a bit suspicious when I first started collaborating with Dieter Fensel, whose work bears all the formal hallmarks of a true neaty. Even more alarming, his primary research goal was to provide sound, formal foundations to the area of knowledge-based systems, a traditional stronghold of the scruffies - one of whom had famously declared it “an art”, thus attempting to place it outside the range of the neaties (and to a large extent succeeding in doing so).