We present a novel, modular, recurrent connectionist network architecture which learns to robustly perform incremental parsing of complex sentences. From sequential input, one word at a time, our networks learn to do semantic role assignment, noun phrase attachment, and clause structure recognition for sentences with passive constructions and center embedded clauses. The networks make syntactic and semantic predictions at every point in time, and previous predictions are revised as expectations are affirmed or violated with the arrival of new information. Our networks induce their own "grammar rules" for dynamically transforming an input sequence of words into a syntactic/semantic interpretation. These networks generalize and display tolerance to input which has been corrupted in ways common in spoken language.

Molecular biology is emerging as an important domain for artificial intelligence research. The advantages of biology for design and testing of AI systems include large amounts of available online data, significant (but incomplete) background knowledge, a wide variety of problems commensurate with AI technologies, clear standards of success, cooperative domain experts, non-military basic research support and percieved potential for practical (and profitable) applications. These considerations have motivated a growing group of researchers to pursue both basic and applied AI work in the domain. More than seventy-five researchers working on these problems gathered at Stanford for a AAAI sponsored symposium on the topic. This article provides a description of much of the work presented at the meeting, and fills in the basic biology background necessary to place it in context.

The Second International Workshop on User Modeling was held March 30- April 1, 1990 in Honolulu, Hawaii. The general chairperson was Dr. Wolfgang Wahlster of the University of Saarbrucken; the program and local arrangements chairperson was Dr. David Chin of the University of Hawaii at Manoa. The workshop was sponsored by AAAI and the University of Hawaii, with AAAI providing eight travel stipends for students.

In 1877 the Italian astronomer number of inferences about what has Program co-chairpersons are Dr. Robin Giovanni Schiaparaelli announced not changed as the result of performing Cohen of the University of Waterloo, the existence of canali on Mars: a network some action A while allowing the Bob Kass of the EDS Center for of straight and curved lines running small number of inferences about Machine Intelligence, and Cecile Paris across the planet. Canali, meaning what has changed as a result of A. of the Information Sciences Institute.

With increases in the complexity of information that must be communicated either by or to computer comes a corresponding need to find ways to communicate that information simply and effectively. It makes little sense to force the burden of communication on a single medium, restricted to just one of spoken or written text, gestures, diagrams, or graphical animation, when in many situations information is only communicated effectively through combinations of media.

We present a novel, modular, recurrent connectionist network architecture of complexwhich learns to robustly perform incremental parsing sentences. From sequential input, one word at a time, our networks learn to do semantic role assignment, noun phrase attachment, and clause structure recognition for sentences with passive constructions and center embedded clauses. The networks make syntactic and semantic predictions at every point in time, and previous predictions are revised as expectations are affirmed or violated with the arrival of new information. Our networks induce their own "grammar rules" for dynamically transforming an input sequence of words into a syntactic/semantic interpretation.

The Workshop on Future Directions in NLP was held at Bolt Beranek and Newman, Inc. (BBN), in Cambridge, Massachusetts, from 29 November to 1 December 1989. The workshop was organized and hosted by Madeleine Bates and Ralph Weischedel of the BBN Speech and Natural Language Department and sponsored by BBN's Science Development Program.

The Workshop on Future Directions in NLP was held at Bolt Beranek and Newman, Inc. (BBN), in Cambridge, Massachusetts, from 29 November to 1 December 1989. The workshop was organized and hosted by Madeleine Bates and Ralph Weischedel of the BBN Speech and Natural Language Department and sponsored by BBN's Science Development Program.

Many barriers exist today that prevent effective industrial exploitation of current and future AI research. These barriers can only be removed by people who are working at the scientific forefront in AI and know potential industrial needs. The Knowledge Processing Laboratory's research and development concentrates in the following areas: (1) natural language interfaces to knowledge-based systems and databases; (2) theoretical and experimental work on qualitative modeling and nonmonotonic reasoning for future knowledge-based systems; (3) application-specific language design, in particular, Prolog extensions; and (4) desi gn and analysis of neural networks. This article gives the reader an overview of the main topics currently being pursued in each of these areas.

J. American Society for Information Science, 41 (6), 391-407.