Artificial Intelligence and the Environment

Montreal, Canada
August, 1995

Sponsored by The International Joint Conference on Artificial Intelligence, NASA Ames Research Center, and The American Meterological Society

This workshop brings together two diverse groups of people with the aim of understanding the potential and problems of applying Artificial Intelligence (AI) technologies to environmental studies and engineering:

  • Researchers and scientists whose goal is to increase our understanding of physical, chemical and biological processes - particularly researchers studying atmospheric, climatic, ecological, oceanic, and solid-earth processes - as well as environmental engineers concerned with problems regarding pollution control, natural disaster planning, and hazardous materials management.

  • AI researchers and practitioners whose goal is to develop and engineer methods for automation and information processing required by environmental applications; for example, novel methods for acquiring sensed data (e.g., Antarctic robotic explorers), systems that assist in processing, archiving, and distribution of increasingly diverse and voluminous sensed data (e.g., as in Earth Observing Systems), modeling earth processes, and planning in data analysis or hazardous waste disposal.

    • The workshop provides an important and timely forum for participating researchers, scientists, and engineers to explore the novel problems environmental studies present, and to examine the fruits of traditional and non-traditional Artificial Intelligence technologies as applied to environmental studies and engineering. The objective of the workshop is to foster discussion, bringing together the experience base of environmental scientists and engineers with the information handling experience of AI theorists and practitioners.

    The workshop will focus on two topics:

  • AI in Environmental Sciences - including hydrological, oceanic and ecological systems studies, earth and climate process prediction, and atmosphere studies.
  • AI in Environmental Engineering - pollution control, natural disaster planning, hazardous materials management

    • Papers

    Miquesl Sanchez "Integrating General Expert Knowledge and Specific Experimental Knowledge in WWTP"

    Yasushi Umeda "The Green Browser: A Proposal of Green Information Sharing and Life Cycle Design"

    Ulrich Heller "A Qualitative Modeling Approach to Algal Bloom Prediction"

    Jeff Rickel "Automated Modeling of Complex Biological and Ecological Systems"

    Byoung-Tak Zhang "Water Pollution Prediction with Evolutionary Neural Trees"

    Richard Verret "Scribe: An interactive System for Composition if Meterological Forecasts"

    Michael N. Huhns "The Enviromental Information Mall"

    Eric K. Jones "Retrieving Structured Spatial Information from Large Databases: A Progress Report"

    Amy Lansky "The Collage/Khoros Link:Planning for Image Processing Tasks"

    Paolo Avesani "Combining Human Assessment and Reasoning Aids for Decision-making in Planning Forest FIre Fighting"

    Leland Ellis "Biodiversity and Ecosystems Network (BENE) -- The Challenge of Building a Distributed Informatics Network for Biodiversity"

    Mandy Haggith "Support for Argumentation in Natural Resource Management"

    Vincent B. Robinson "KBLIMS for Forested Ecosystem simulation Management"

    Keith Wichman "OODBMS, Archive/Retrieval"

    Jon W. Robinson "Automating the Detection of Enviromental Crime"

    Cindy Mason "An Intelligent Assistant for Nuclear Test Ban Treaty Verification"

    Stan Matwin "Planning with Agents in Intelligent Data Management for Forestry"

    Georgio Brajnik "Introducing Boundary Conditions in Semi Quantitative Simulation"

    Bruce Barkstrom "The EOSDIS Production Environment: Distributed Capacity Management and Production Scheduling"

    Cindy Mason
    cmason@cs.berekeley.edu