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Bayesian updating in causal probabilistic networks by local computations

Combining replicated real-world experiments, which take advantage of implemented mitigation measures or other forms of human impact, with research-led experimental manipulations can provide powerful scientific tools for inferring causal drivers of ecological change and the generality of their effects.Additionally, combining these two approaches can facilitate communication with stakeholders involved in implementing management strategies.

bayesian updating in causal probabilistic networks by local computations-25

Assessment: 80.0% Coursework, 20.0% Practical Level: 6 Timetable: Credits: 30.0 Contact: Ms Laura Edgar Overlap: None Prerequisite: None Write a 10,000 word dissertation on a particular topic within a subject area of the computer and communications programme. Students will have two terms to write up and submit the dissertation.The initialization involves dedicated operations not shared by inference operations according to existing methods.We show that the new inference operations presented here unify inference and initialization.TY - JOURT1 - Bayesian updating in causal probabilistic networks by local computations AU - Jensen, Finn V. An object-oriented version of the computational scheme in S. Second, in the worst case, the DFS algorithm explores the search space of all elimination orders, which has size n!Human-induced environmental changes are causing major shifts in ecosystems around the globe.

To support environmental management, scientific research has to infer both general trends and context dependency in these shifts at global and local scales.

Assessment: 100.0% Dissertation Level: 7 Credits: 30.0 Contact: Ms Laura Edgar Overlap: None Prerequisite: None Write a 10,000 word dissertation on a particular topic within a subject area of the computer and communications programme. Students will have two terms to write up and submit the dissertation.

Assessment: 100.0% Dissertation Level: 7 Credits: 15.0 Contact: To Be Confirmed Overlap: None Prerequisite: None This module will provide students with a good understanding of the causes, course and consequences of the Norman Conquest of England in 1066 which decisively shifted England¿s relations with continental Europe from a Scandinavian to a Norman French focus. The first explores the last decades of Anglo-Saxon England including links between England and Normandy before 1066; the second investigates the succession crisis of the 1060s, the invasion of 1066 and the subsequent resistance and rebellions while the third addresses the impact of the Norman Conquest on different aspects of government and society, including landholding and lordship, the church and the physical landscape.

Multiply sectioned Bayesian networks (MSBNs) provide a coherent and flexible formalism for representing uncertain knowledge in large domains.

Global consistency among subnets in an MSBN is achieved by communication.

We demonstrate such an integrative approach using the case study Eco Impact, which aims at empirically unravelling the impacts of wastewater-born micropollutants on aquatic ecosystems.