Reasoning About Actions for the Management of Urban Wastewater Systems: Preliminary report

  • Authors:

  • Juan Carlos Nieves;Montse Aulinas;Ulises Cortés

  • Affiliations:

  • Knowledge Engineering and Machine Learning Group, Technical University of Catalonia, Barcelona, Spain;Knowledge Engineering and Machine Learning Group, Technical University of Catalonia, Barcelona, Spain and Laboratory of Chemical and Environmental Engineering, University of Girona, Spain;Knowledge Engineering and Machine Learning Group, Technical University of Catalonia, Barcelona, Spain

  • Venue:
  • Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
  • Year:
  • 2009

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Abstract

It is well-known that the management of Urban Wastewater Systems (UWS) is a complex and critical process. To decide which is the correct sequence of actions for managing a given circumstance it is necessary a sophisticated analysis of hypothetical impact of these. Hence, the design of intelligent systems able to perform temporal projections based on the description of actions could help to deal with risk scenarios. In this paper, we propose to use recent developments in knowledge representation languages and non-monotonic reasoning methodologies for representing and reasoning about actions for the Management of Urban Wastewater Systems. To this end, we explore the use of an action representation language called A for reasoning about the actions in the management of UWS. In particular, we consider the problem of industrial discharges. We present a declarative representation of a transition function from states and actions to states which allows us to make conclusions about a particular situation that may arise if one performs a particular sequence of actions.