zbMATH — the first resource for mathematics

Logic-based decision support for strategic environmental assessment. (English) Zbl 1209.68092
Summary: Strategic Environmental Assessment is a procedure aimed at introducing systematic assessment of the environmental effects of plans and programs. This procedure is based on the so-called coaxial matrices that define dependencies between plan activities (infrastructures, plants, resource extractions, buildings, etc.) and positive and negative environmental impacts, and dependencies between these impacts and environmental receptors. Up to now, this procedure is manually implemented by environmental experts for checking the environmental effects of a given plan or program, but it is never applied during the plan/program construction. A decision support system, based on a clear logic semantics, would be an invaluable tool not only in assessing a single, already defined plan, but also during the planning process in order to produce an optimized, environmentally assessed plan and to study possible alternative scenarios. We propose two logic-based approaches to the problem, one based on Constraint Logic Programming and one on Probabilistic Logic Programming that could be, in the future, conveniently merged to exploit the advantages of both. We test the proposed approaches on a real energy plan and we discuss their limitations and advantages.
68N17 Logic programming
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
Cbc; CP-logic
Full Text: DOI
[1] Schiex, Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI 95 pp 631– (1995)
[2] Sorensen, Procedures and Programs to Assist in the Impact Statement Process. (1973)
[3] Santos Costa, Conference on Uncertainty in Artificial Intelligence (2003)
[4] DOI: 10.1093/jigpal/jzp025 · Zbl 1189.03039 · doi:10.1093/jigpal/jzp025
[5] DOI: 10.1145/129393.129398 · doi:10.1145/129393.129398
[6] DOI: 10.1007/978-3-540-89982-2_54 · Zbl 1185.68178 · doi:10.1007/978-3-540-89982-2_54
[7] DOI: 10.1016/0743-1066(94)90033-7 · Zbl 00639141 · doi:10.1016/0743-1066(94)90033-7
[8] DOI: 10.1007/978-3-540-74782-6_11 · Zbl 05314990 · doi:10.1007/978-3-540-74782-6_11
[9] DOI: 10.1007/978-3-540-68679-8_14 · Zbl 1143.68379 · doi:10.1007/978-3-540-68679-8_14
[10] DOI: 10.1016/S0004-3702(97)00027-1 · Zbl 0902.03017 · doi:10.1016/S0004-3702(97)00027-1
[11] DOI: 10.1007/978-3-642-04244-7_2 · Zbl 05612634 · doi:10.1007/978-3-642-04244-7_2
[12] Pearl, Causality (2000)
[13] DOI: 10.1002/(SICI)1097-4571(2000)51:2&lt;95::AID-ASI2&gt;3.0.CO;2-H · doi:10.1002/(SICI)1097-4571(2000)51:2<95::AID-ASI2>3.0.CO;2-H
[14] DOI: 10.1007/11564751_46 · Zbl 05323085 · doi:10.1007/11564751_46
[15] Meert, Proceedings of the 19th International Conference on Inductive Logic Programming (2009)
[16] De Koninck, WLP pp 91– (2006)
[17] Dantsin, Proceedings of the 2nd Russian Conference on Logic Programming pp 152– (1991)
[18] DOI: 10.1145/256303.256306 · Zbl 0890.68032 · doi:10.1145/256303.256306
[19] Zhou, IEA/AIE pp 790– (1996)
[20] Vennekens, International Conference on Logic Programming pp 195– (2004) · doi:10.1007/978-3-540-27775-0_14
[21] DOI: 10.1017/S1471068409003767 · Zbl 1179.68025 · doi:10.1017/S1471068409003767
[22] Sato, International Joint Conference on Artificial Intelligence pp 1330– (1997)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.