# Call for Abstracts and Participation

Seventh Annual Conference of the Australasian Bayesian Network Modelling Society (ABNMS 2015)

November 23 - 24, 2015: Pre-Conference Tutorials

November 25 - 26, 2015: Conference

Monash University, Caulfield Campus, Melbourne

The organising committee for ABNMS 2015 is pleased to invite the submission of abstracts.

Abstracts are invited from all fields. Past presentations have covered a wide range of disciplines including environmental management, geology, law, ecology and medicine, and a variety of technical aspects on methods of development, data mining, linking GIS with Bayesian Networks, and lessons learned from particular BN projects.

Those beginning to use Bayesian networks are invited to present prospective projects for discussion.

Key Dates

• Call for abstracts: 31 July 2015
• Abstract submission deadline: 4 September 2015
• Decision on abstracts: 11 September 2015
• Deadline for conference registration (including pre-conference tutorials): 21 September 2015

Abstracts for ABNMS 2015 should be no longer than 300 words. Please submit your abstracts via https://www.easychair.org/conferences/?conf=abnms2015

Include the title of your presentation, authors, affiliations, contact details for the corresponding author and abstract. The abstract should be self-contained and explicit, covering the aims, methods, results and main conclusions of the work. The abstract should not contain figures, tables or references.

## Travel Grants

The Australasian Bayesian Network Modelling Society (ABNMS) is offering 4 travel grants to attend the ABNMS Tutorials and Conference 23-26 November 2015 Melbourne, Australia. Awards will be for $250 to$500 to contribute to the costs of travel to and from the conference.

Three Student Grants will be awarded and one 2015 Travel Grant for any person who attended the ABNMS pre-conference tutorials in 2014 in Rotorua, New Zealand and will present in 2015.

Applications should include a brief statement indicating the type of travel grant being applied for, justifying the application, an estimate of travel costs, a scanned signed statement from an academic supervisor verifying student status (if in application for one of the student travel grants), and a CV. An abstract of the talk to be presented at the conference must be submitted in parallel (see above). Student travel grants will only be awarded if the recipient registers for the conference and tutorials. Please note the 2015 Travel Grant recipient is not required to register for the pre-conference tutorials.

Travel grant applications must be submitted by email to president@abnms.org by 20 September 2014.

If you have any questions regarding ABNMS2015, please email ABNMS2015@abnms.org.

# Melbourne Bayesian Network Training Workshop in June

We are pleased to announce that we will be holding our Introduction to BNs workshop in Melbourne on June 18-19th at Monash University's Caulfield campus. This is an excellent opportunity to learn the foundations of Bayesian networks, common extensions and connect with others in using the techniques.

If you would like to attend, please register at the following site:

http://bayesian-intelligence.com/training/

There you will also find a draft workshop schedule with an overview of the topics covered. If you are unable to make these dates, please email me indicating your interest in attending at another time.

For more general information about our workshops, you can visit http://bayesian-intelligence.com/training/ where you will find contact info.

Finally, please also feel free to pass this email on to anyone you know that may be interested in attending our BN training courses.

Regards,
Owen Woodberry

# Bayesian Network Training Workshops

Due to demand, we are pleased to announce that we will be holding two two-day Introduction to BNs workshops in February: in Melbourne on February 12-13th, and in Townsville on February 26-27th.  This is an excellent opportunity to learn the foundations of Bayesian networks, common extensions and network with others in using the techniques.

If you would like to attend either of the sessions, please register at the following site:

http://bayesian-intelligence.com/training/

There you will also find a draft workshop schedule with an overview of the topics covered. If you are unable to make these dates, please email indicating your interest in attending at another time.

For more general information about our workshops, you can visit http://bayesian-intelligence.com/training/ or contact Owen Woodberry at owen.woodberry@bayesian-intelligence.com.

# De-teching Australia: Australia torpedoes its own future, blowing up science, technology and education

— Kevin B Korb

The Australian government is undermining the future of Australia by attacking science and technology research and education on a massive scale, leading Australia in a unique act of self-immolation. It is not hard to see that the future economic well-being of developed countries is intimately linked to the three key supports of modern economies: science, technology and education. This government is actively attacking all three and is also actively campaigning against all three in the media, especially through its cheerleaders in the Murdoch press.

These are some of the notable attacks on science, technology and education enacted, proposed or supported by the ministers of the Abbott government:

• Attacking the Internet in Australia by cutting the fibre-optic based National Broadband Network project started by the Labor government. Instead of fibre optics, Minister for Communications Malcolm Turnbull advocates the retention of slower, older and more maintenance-intensive copper wire connections to homes and businesses. As iinet likes to advertise, Australia is behind Romania in average Internet access speeds. Turnbull's program will keep Australia well behind the OECD average for the foreseeable future. Neither Turnbull nor Abbott have a clue that the Internet has become a key enabler of current economic growth. Watch this incredible performance by the pair of them, laughing about the Internet being a "video entertainment system". Or, watch Turnbull in this whiteboard "explainer" on how the value of the NBN in 2030 should be assessed based on the values of 2014. These are the current leaders of our government!
• Cutting science research, in particular the government is cutting funding to the Australian Research Council by around $29M per year (about 5%), to CSIRO by$86M (about 6%), to DSTO by $48M (about 10%), and to the Cooperative Research Centre program by$25M (about 14%). There are hints that more cuts are to come. These programs have been the source of much of the innovation in Australia, so their winding down will kill off what was already a weak contributor to the economy.
• Cutting university and school funding. \$30 billion has been cut from school funding, by dropping the "Gonski" reforms that Abbott previously committed to implementing. University funding per student is being cut 20%. As the OECD's Education at a Glance documents year in and year out, public education is central to economic well being; these cuts will lead Australia to the bottom of the OECD not just in education but also in future economic performance.

Many university administrators have been gulled into supporting this by the lure of the deregulation of university fees. While it may be possible for universities to make up the funding cuts by raising fees to students, it is hardly obvious that it will happen, since many students may turn away from accepting life-burdening debts in return for an education. In any case, this will increase inequality of access to education and undermine education's role in driving future economic prosperity.

• Supporting the Defence Trade Controls Act (DTCA) 2012, which will soon criminalize a large swathe of ordinary research and education in medicine, science and technology, all of which have supported economic growth in Australia for many decades.

The law was amended in a minor way in 2012 to enable a "Steering Group" led by Chief Scientist Ian Chubb to review and make recommendations for changes over a two-year period. That is why the legislation is only coming into force in May, 2015. Chubb appears to be a useful idiot for the government: his enlarged opinion of his own ability to effect changes to the law has been widely accepted within academia, with the result that many or most academic leaders have reacted with supreme complacency to the DTCA. As the drop-dead day comes nearer, we can expect more and more academics to realize that they are being turned into criminals. The NTEU has recently launched an educational campaign to inform an academic community that is still mostly asleep.

• Cutting funding for the ABC and SBS. The ABC has been stripped of the Australia Network, which has been handed over to Sky News Australia, partly owned by Murdoch. This is despite the fact that the Australia Network has been a very well received broadcaster to our near neighbors for decades, providing valuable good will for our diplomatic and trading interests. Furthermore, after heavy campaigning by the Murdoch press, both public broadcasters are having their funding cut, with threats continuing of larger cuts in the future. Turnbull claims "efficiency savings" are always possible. Were that true, budgets could always be cut to zero, matching his apparent IQ.

The dramatic budget cuts are explained by Joe Hockey and Tony Abbott as being "necessary" to save Australia from a budget crisis inherited from the Labor government, as well as being dictated by fairness in spreading the burden of this salvation across the community. Although many economists have publicly denounced the claim of Australia being in budgetary crisis as nonsense, it is no surprise that the Australian public have largely seemed to swallow it whole. The Big Lie worked very well for the Nazis, and it is working very well for the Coalition government. After all, the Murdoch press controls most of the print news in Australia and very clearly sets the direction of public debate. Big Lies repeated over and over begin to seem like common knowledge rather than common nonsense.

Abbott claims his government needs no minister for science. He claims to be able to represent the portfolio unassisted. However, his understanding and interests are inimical to science, technology and education and to the long-term interests of Australia. He infamously denounced the scientific consensus on global warming as "absolute crap". He seems to view science as a convenient source of opinions, when scientists happen to agree with him, and otherwise as a nuisance. The long history of science supplying the ideas and means for engineering and technological development from the beginning of western civilization means nothing to him; instead, Abbott and his ministers prefer to attribute that history of civilization to Christianity. Theirs is a view that would have been well received in the Dark Ages.

If anyone is going to lead Australia into a new Dark Age, it is Abbott and his government: the terrorism of ISIS is nothing compared to the terrorism of our own government.

# Australia's Act of Intellectual Terrorism: DTCA 2012

— Kevin B Korb

In October 2012 the Australian parliament passed the Defence Trade Controls Act. The stated purposes of the act are unobjectionable: implementing the prior Australia-United States Defense Trade Cooperation Treaty, simplifying defence-related trade between Australia, the US and the UK, and tightening the regulation of intangible transfers of military goods, reflecting the growth of the internet in communications. Unfortunately, these good intentions have led the Australian government to adopt an extraordinarily broad definition of military goods and to impose an impossibly harsh regulatory regime on activities concerning them, to the point that what is today ordinary academic research into, for example, Bayesian network technology may tomorrow become a criminal activity subject to 10 years imprisonment. It is an act that can legitimately be called intellectual vandalism. Indeed, some academics have already abandoned long-pursued research projects out of fear of the Act being used for retribution, making it a means of intellectual terrorism.

## The Defence and Strategic Goods List

One support for the act is the Defence and Strategic Goods List (DSGL). The DSGL lists goods targeted for regulation that are strictly military and also many goods which could be put to military uses, so-called dual-use goods. These latter include a huge variety of things, including: bacilli and viruses, plant pathogens, metallic alloys, carbon fibres, neural computers, optical computers, vector and other high-performance computers, optical telecommunications, signal processors, fault-tolerant systems,1 image processing, cryptography, and, of most interest to us, robotics. The DSGL explicitly incorporates all software which is designed or modified for the "development, production or use" of the goods. This means that all software that may be used to drive robots are covered by the list and by the Act using the list: all software that can be used for intelligent decision making and analysis, which clearly means all of Bayesian network technology, not to mention all of computational statistics, data mining and artificial intelligence generally.

The Act's intent is to regulate foreign access to new research in military and dual-use goods. While all of the dual-use goods could potentially be used in military applications and controlling such uses is a worthwhile objective, all of them also are used in non-military business, industry and governance, and these civilian uses are vital to the economy and prosperity of the nation. Therefore, a reasonable balance must be struck between supporting research in these areas and controlling access to the research. As the Act stands, it is clear to us that these matters are not in balance.

## Australia Prepares to Eat its Brains

A key feature of the Act is that it requires prior permission to communicate new research to a foreign national in any of the nominated areas. This includes, but is hardly limited to, publishing research in academic journals. As many submissions on the bill to the Senate Committee on Foreign Affairs, Defence and Trade point out, this requirement implies that the Department of Defence (DoD) would need sufficient expertise across all of the domains listed in the DSGL to judge whether or not proposed research would require a permit. Plausibly, this is a level of expertise which the DoD does not have, nor will ever have. But the difficulties with the Act go far beyond the need to hire thousands of experts to make permit judgments upon research and education.

Obtaining prior approval for each research project and, possibly, each research communication would put an end to a very large amount of research activity in Australia, directing researchers, students and subsequent economic activity elsewhere. Permission would be required to publish across a huge range of areas under active research in the university sector. Without a clear opportunity to publish, most academics would choose not to undertake research projects in these areas, meaning that ARC and NHMRC projects would not even begin without prior approval from the Department of Defence. The Act provides no guidance as to how the DoD should make judgments about research which has yet to be conducted. Many ongoing collaborations with overseas institutions would need separate approvals or would cease. Since about half of enrolled postgraduate students are foreign nationals, for the most part without permanent residency, the requirement for prior permission to communicate new research to them would also cripple postgraduate coursework.

A minor point is that there seems to be some unclarity about whether or not foreign students can be taught anything on the DSGL without prior permission. The Chubb Steering Group's (more on them below) report on its 12 April 2013 meeting states that "the Australian export control system only regulates transfers from a person inside Australia to a person outside Australia". However, the Defence Department's Explanatory Memo for the Bill states that communications are regulated "if the supply is from an Australian person to a foreign person regardless of their geographical location" and "the provision occurs in Australia to a foreign person". Re-skimming the Act itself  (96 pages of gripping prose) unfortunately failed to reveal who's right. Still, the considerations immediately below mean this issue is well and truly dominated by other problems.

PhD and Masters theses have always been published by the institutions granting them; in consequence of the Act, either this practice would have to be abandoned, and the contents of theses in the nominated areas suppressed — which would certainly give Australian research a unique voice in the world — or prior approval for publishing as-yet uncreated new research would have to be obtained. Note that this restriction would apply to all postgraduate thesis work in dual-use domains, not just that involving foreign students.

As a crude index of how the Act unaltered will impact the activities of my own organization, the Faculty of IT at Monash University, I surveyed all masters level coursework units (5000 series units, ignoring thesis units) for topics proscribed by the Act (i.e., found in the DSGL). Note that it is an imperative that researchers who teach (which describes myself and almost all of my teaching colleagues at Monash) should incorporate new research into their own teaching. Of necessity, therefore, if a topic matches a dual-use good, it is regulated by the Act. By my count 18 out of 61 classes would come under the provisions of the Act, requiring prior permission for each international student enrolled. (The DoD Explanatory Memorandum makes it clear that individual permission is required — short of Ministerial intervention!) The main areas impacted are: security, software usable for controlling robots, telecommunications technology and high-performance computing. No doubt a similar proportion of our degree by research topics would have to be pre-approved or abandoned. The disruption to Monash FIT’s educational activities will be severe.

## The Strengthened Export Controls Steering Group to the Rescue

Amendments to the Bill were proposed by the Senate Foreign Affairs, Defence and Trade Committee in October 2012 which would appear to be sufficient protection for the ongoing research and educational activities of the tertiary sector. Alternative amendments might be derived from the UK Export Controls Act, which again protect public research and education. The corresponding US International Traffic in Arms Regulations also contain a corresponding exclusion, Section 120.11. The Australian Act contains no such protection (despite the extraordinary gobbledygook produced by the US Ambassador to Australia on the subject; see item 8 on the Committee's submission page). The accompanying Explanatory Memorandum does list some exemptions, relying upon the DSGL. The DSGL exempts technology that is in the public domain, required for patents or is basic scientific research. The Department of Defence reckons that this is sufficient protection for tertiary education and research: "With the exemptions ... Defence anticipates that these controls will apply only to very specialised and high-end research" (Explanatory Memo). There are a few substantial problems with this thinking, however. The administrative burden of deciding what is already public and what is not, covering individual research publications over something like 1/3 of Australia's engineering and IT work, would probably suck up a significant percentage of Australian GDP forever. Actual scientific research, while building upon what is in the public domain lives and grows according to what it adds that is new, and so it will not generally be public domain. However, according to the Defence Explanatory Memo (footnote 16), basic scientific research excludes research "directed towards a specific practical aim or objective." So, presumably university research is in the clear. What perhaps eludes Defence experts is that a very large amount of research at universities does have a practical aim or objective. Indeed, the endless waves of "Excellence of Research in Australia"-like programs that regularly inundate academic life here are always trying to pump out information about the wider impact of research on the community. Academics are constantly being badgered to prove that their research has near-term practical impacts and objectives. I suppose an unintended salutary effect of the Bill could be to discourage academics from focusing too much on the immediate benefits of their work! Be that as it may, probably most university research comes with intended applications, and so is covered by the legislation.

In consequence researchers right now must reckon with the possibility that the communication of their efforts, whether in teaching, supervision or publication, may result in 10 years in prison.

Many parties to the discussions, such as Universities Australia and the National Tertiary Education Union, have noted the disparity in protections offered by the UK and the US compared with that on offer in the DTCA for Australians. The consequence of their raising their concerns has been a suspension of enforcement of the Act for two years and the founding of the Strengthened Export Controls Steering Group, headed by Australia's Chief Scientist Ian Chubb, to investigate and test the consequences of the Act with pilot studies. The Steering Group has roughly equal representation from Defence (and Defence industry) and academia. They are empowered to make recommendations. Some people appear to think this answers all of the concerns raised above about the legislation. But until concrete recommendations are made, and rather more importantly, acted upon by Parliament, the university sector is operating in the dark. We do not know which of our research and pedagogical activities will in the near future be prosecuted as criminal. Given that now simply posting classified information on the internet in the public interest is being trumpeted as "assisting the enemy" (Julian Assange, Edward Snowden), it is not much of a stretch to imagine the publication of research on ordinary, but dual-use, technology soon being called assisting the enemy as well.

Three outcomes seem now to be possible: (1) the law may be revised to accord with the corresponding legislation in the US and the UK; (2) the law may be left as is, but its provisions not enforced with regard to most research of a non-military nature; (3) the law may be left as it is, and its provisions enforced in a wide-ranging way. If the first option is realized, then the research and teaching environment will remain much as it has been, and the Australian nation may get on about its business. If option (3) is realized, a large portion of Australian research will simply stop. The tertiary education sector will be massively disrupted and its international reputation will collapse, outside of fields which would appear to be free of the regulations implied by the Act, such as the Arts. Much of engineering, the physical and medical sciences, and information technology would be finished in Australia. Option (2) implies less immediate impact. However, the continuing possibility and threat that an administration has only to change its mind about enforcement would have a significant chilling effect on many researchers. The choice of research area would have to weigh the opportunity for administrative interference and the ultimate potential for criminal sanctions should a researcher or her or his research rub the DoD or the government of the day in the wrong way. Over the long term, research and education in Australia would be severely crippled.

Bayesian Intelligence finds that the unamended Defence Trade Controls Act 2012:

• Fails to provide the same safeguards for research and educational activity to be found in the corresponding legislation enacted in the UK and the USA

• Will handicap research and tertiary educational activities across a wide range of domains in engineering, information technology, science and medicine

• Is likely to lead to a diversion of world-class researchers, students and projects outside of Australia

The introduction of a two-year transition period in the final Act defers, but leaves unaltered, these bad consequences. In view of these probable deleterious effects, Bayesian Intelligence, as a company dependent upon new research in a dual-use technology, strongly urges that the legislation be amended as soon as possible to incorporate similar protections to those in the corresponding legislation of the UK and the US.

1 CORRECTION: Originally, I had the following parenthesis here: "(including computers with error-detecting memories, which long ago became nearly universal)". However, I have in the meantime noticed that the DSGL has an explicit exclusion for this case, in Note a of 4A003.a on p. 165. My apology for not noticing this in the first place.

# Bayes by the Bay, Chennai, India, 2013

Kevin B Korb

The Chennai Institute of Mathematical Sciences held its 50th birthday party in Pondicherry, India, 4-8 January 2013, organized by Ronojoy Adhikhari and Rahul Siddharthan. This was a lively meeting attended by statisticians, physicists, biologists, climate scientists, computer scientists and others, united by an interest in applying Bayes Theorem in solving all kinds of scientific problems — and divided, as usual, by the many possible interpretations of Bayes Theorem. I look forward to the day(?) when Bayesians can find consensus, not over what in particular probabilities may be, but over the fact that they may be diverse things. Acknowledging objectivity needn't come at the price of abandoning subjectivity (see, e.g., David Lewis's "A subjectivist's guide to objective chance" in R. Jeffrey (ed) Studies in Inductive Logic and Probability, vol III, 1980).

In any case, there were many interesting presentations and discussions, including, among many others: Devinder Sivia (Oxford) presenting Bayesian methods of data analysis, Rajesh Rao (Washington) describing recent Bayesian models of brain function, Erik van Nimwegen (Basel) using Bayesian networks to predict protein contacts, Balaji Rajagopalan (Colorado) analysing climate change with extreme value models. I gave talks on Bayesian network modeling, causal discovery of Bayesian nets, and discretization. Most of these were filmed and will be made available on Youtube. When that happens, I'll update this post.

# The 9th Bayesian Modelling Applications Workshop

Ann E Nicholson

The proceedings of our recent workshop on applying Bayesian networks to real-world problems will be coming out soon (a preliminary version is available for on-line viewing here). The workshop was co-located with the 28th Conference on Uncertainty in Artificial Intelligence (UAI 2012), on Catalina Island, California on August 18, 2012.

Bayesian networks are by now a well-established technology for reasoning under uncertainty, supported by numerous mature academic and commercial software tools. They are being applied in many domains, for example, environmental and ecological modelling, bioinformatics, medical decision support, many types of engineering, robotics, military, financial and economic modelling, education, forensics, emergency response, and surveillance. This workshop solicited submissions describing real-world applications, whether as stand-alone BNs or BNs embedded in larger software systems. We suggested authors address the practical issues involved in developing the applications, such as knowledge engineering methodologies, elicitation techniques, defining and meeting client needs, validation processes and integration methods, as well as software tools to support these activities.

The resultant workshop included presentations on a good variety of applications, including oil drilling, managing river catchments, analysing HIV mutations, gang violence, and understanding students' reading comprehension. Many of the applications responded to a workshop theme by illustrating models of temporal reasoning, using dynamic Bayesian networks (DBNs), continuous-time Bayesian networks (CTBNs) and partially observable MDPs (POMDPs).

The workshop demonstrated an active and growing community of modellers taking what were until recently research techniques for Bayesian modelling and applying them to solving a diverse range of important problems in the wider community.

# How to Model with Bayesian Networks

—Ann E Nicholson

Since Bayesians without Borders will in significant part be about Bayesian networks and their uses, in this post I will introduce them to newcomers to the technology.

Bayesian networks (BNs) are an increasingly popular technology for representing and reasoning about problems in which probability plays a role. A Bayesian network is a directed, acyclic graph whose nodes represent random variables and arcs represent direct dependencies. The arcs often, but not always, also represent direct causal connections between the variables. The nodes pointing to $X$ are called its parents and collectively are denoted $\pi(X)$. The relationship between variables is quantified by conditional probability tables (CPTs) associated with each node, namely $P(X|\pi(X))$. The CPTs together compactly represent the full joint distribution. Users can set the values of any combination of nodes in the network that they have observed. This evidence, $e$, propagates through the network, producing a new posterior probability distribution $P(X|e)$ for each variable in the network. There are a number of efficient exact and approximate inference algorithms for performing this probabilistic updating, providing a powerful combination of predictive, diagnostic and explanatory reasoning.

I will illustrate with the design of a BN for a simplified version of a real ecological problem, modeling native fish populations in Victoria. Problem: A local river with tree-lined banks is known to contain native fishpopulations, which need to be conserved. The river passes through croplands and is susceptible to drought conditions. Rainfall helps native fish populations by maintaining water flow, which increases habitat suitability as well as connectivity between different habitat areas. However, rain can also wash pesticides that are dangerous to fish from the croplands into the river. What we want to do is build a BN adequate for modeling this system.

The first step is to decide what the variables of interest are, which will become the nodes in the BN. The abundance of native fish directly depends only on the level of pesticide in the river and the river flow, hence Native Fish Abundance — a so-called "leaf node" — has only those two parent nodes. RiverFlow depends on how much rain falls in a given year (Annual Rainfall), and how much of that water ends up in the river, which means it depends also on the long term Drought Conditions. The amount of pesticide in the river (Pesticide in River) depends on Pesticide Use and whether there is enough rain (Annual Rainfall) to wash it into the river. Finally, the condition of the trees on the river bank depends only on the long term drought and more recent rainfall.

This graphical structure captures these causal interactions:

In consultation with an ecologist we might build the CPTs (i.e., eliciting the parameters from the ecologist), as in these example tables:

Note that Pesticide Use (just "Pesticides" in the table) and Annual Rainfall are so-called "root nodes" with no parents, so there is only a single probability distribution for each, whereas for nodes with parents there is a conditional distribution for each possible instantiation of its parents.

The CPT for the Native Fish Abundance node shows the possible combinations of values for the parent nodes (Pesticides and River Flow), and a probability distribution of the resultant Native Fish Abundance, over the three levels, High, Medium and Low. We can see that the best conditions for the fish are Low levels of pesticide and Good River Flow (.8, .15, 0.05), while the worst are High pesticide use and Poor River Flow (.01, .10, .89). Note also that there may well be other factors in play, such as the presence of exotic predators, or disease, that are not represented explicitly by nodes in the BN. The effects of these are averaged over in the CPTs. They are reflected, for example in the 0.05 probability that native fish abundance is Low, even under the best pesticide and river flow conditions.

Now that we have the BN structure and its parameters, the BN can be used for reasoning. That is, we can instantiate different possible scenarios by updating the values of particular nodes and then updating the BN, using one of the many Bayesian network programs around, such as Netica. First, here is the network with no evidence:

Without making any observations, this BN tells us that the most likely state of the native fish is Low abundance (57.8%), though the Tree Condition is most likely Good (53.3%). If we add observations of the root nodes in the BN, when there is High pesticide use, above average rainfall and no drought conditions, we get:

This reasoning is predictive, from cause to effect. In this scenario, the prediction is that the Native Fish Abundance will improve, due to the River Flow being Good, despite the increased Pesticide in River. Alternatively, the BN can be used for diagnosis, by entering evidence for the Native Fish Abundance leaf node:

Comparing to the no evidence case, we can see that it is less likely that the pesticide use was high, less likely there have been drought conditions, and more likely that rainfall has been above average. Finally, we can use the BN in any arbitrary combination of diagnostic and predictive reasoning; here with evidence entered for both a cause (Pesticide Use being High) and an effect (Native Fish Abundance being High), resulting in (fairly small) changes to the distributions for all the other nodes:

Here I have briefly described and illustrated the usual knowledge engineering process of building Bayesian networks. There is, of course, a great deal more to it when building a real network of any complexity, which you can read about in depth in our book Bayesian Artificial Intelligence. Some of these, including causal discovery algorithms for learning BNs from sample data, will also be discussed in future posts in this blog.