Abstract
Analytic techniques proposed for distortion analysis are shown not to predict adequately the higher order terms generated by a semiconductor laser diode of relevance to the design and dimensioning of subcarrier multiplexed optical communications systems. A modified analysis which avoids this deficiency is outlined and illustrative results are presented.

Abstract
Independent and-parallelism, dependent and-parallelism and or-parallelism are the three main forms of implicit parallelism present in logic programs. In this paper we present a model, IDIOM, which exploits all three forms of parallelism in a single framework. IDIOM is based on a combination of the Basic Andorra Model and the Extended And-Or Tree Model. Our model supports both Prolog as well as the flat concurrent logic languages. We discuss the issues that arise in combining the three forms of parallelism, and our solutions to them. We also present an implementation scheme, based on binding arrays, for implementing IDIOM.

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Abstract
Temporal reasoning is recognized as a key problem in many Al areas, namely knowledge bases, natural language processing and planning. The ability to deal with partial knowledge is particularly important in a temporal domain. We describe a temporal language that accounts for incompletely specified temporal information about propositions. The language is semantically based on the notion of maximal interval, the denotation of a proposition being a set of maximal intervals where it holds. The main differences between classical formalisms such as those by Allen, McDermott, Shoham and Kowalski and our approach are briefly discussed. In a partial KB, abduction on the temporal order is generally needed to answer a query, and the answer is then conditional on the abduced facts. To comply with the intended semantics, an implicit form of temporal consistency has to be enforced, and this presents the main challenge to the design of the inference mechanism. We present here the syntax and declarative semantics of a propositional version of the language of maximal intervals and a first discussion of the problems in designing an inference system adequate to work with this temporal framework.

Abstract
The paper begins with the discussion on why we should be concerned with machine learning in the context of distributed AI. The rest of the paper is dedicated to various problems of multi-agent learning. First, a common framework for comparing different existing systems is presented. It is pointed out that it is useful to distinguish when the individual agents communicate. Some systems communicate during the learning phase, others during the problem solving phase, for example. It is also important to consider how, that is in what language, the communication is established. The paper analyses several systems in this framework. Particular attention is paid to previous work done by the authors in this area. The paper covers use of redundant knowledge, knowledge integration, evaluation of hypothesis by a community of agents and resolution of language differences between agents. © Springer-Verlag Berlin Heidelberg 1991.

Abstract