Chancellery Research - Research Publications
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ItemNo Preview AvailableGenerating Dynamic Kernels via Transformers for Lane Detection(IEEE, 2023-01-01)
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ItemNo Preview AvailableImmediate Text Search on Streams Using Apoptosic Indexes(SPRINGER INTERNATIONAL PUBLISHING AG, 2022)
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ItemNo Preview Available'Knowing Whether' in Proper Epistemic Knowledge Bases(AAAI Press, 2016)Proper epistemic knowledge bases (PEKBs) are syntactic knowledge bases that use multi-agent epistemic logic to represent nested multi-agent knowledge and belief. PEKBs have certain syntactic restrictions that lead to desirable computational properties; primarily, a PEKB is a conjunction of modal literals, and therefore contains no disjunction. Sound entailment can be checked in polynomial time, and is complete for a large set of arbitrary formulae in logics Kn and KDn. In this paper, we extend PEKBs to deal with a restricted form of disjunction: 'knowing whether.' An agent i knows whether Q iff agent i knows Q or knows not Q; that is, []Q or []not(Q). In our experience, the ability to represent that an agent knows whether something holds is useful in many multi-agent domains. We represent knowing whether with a modal operator, and present sound polynomial-time entailment algorithms on PEKBs with the knowing whether operator in Kn and KDn, but which are complete for a smaller class of queries than standard PEKBs.
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ItemNo Preview AvailablePlanning for a Single Agent in a Multi-Agent Environment Using FOND(AAAI Press, 2016)Single-agent planning in a multi-agent environment is challenging because the actions of other agents can affect our ability to achieve a goal. From a given agent's perspective, actions of others can be viewed as non-deterministic outcomes of that agent's actions. While simple conceptually, this interpretation of planning in a multi-agent environment as non-deterministic planning remains challenging, not only due to the non-determinism resulting from others' actions, but because it is not clear how to compactly model the possible actions of others in the environment. In this paper, we cast the problem of planning in a multiagent environment as one of Fully-Observable Non-Deterministic (FOND) planning. We extend a non-deterministic planner to plan in a multi-agent setting, allowing non-deterministic planning technology to solve a new class of planning problems. To improve the efficiency in domains too large for solving optimally, we propose a technique to use the goals and possible actions of other agents to focus the search on a set of plausible actions. We evaluate our approach on existing and new multiagent benchmarks, demonstrating that modelling the other agents' goals improves the quality of the resulting solutions.
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ItemSocial planning for social HRI(arxiv, 2016)
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ItemThe Role of Data in a Rapid and Coordinated Response to Infectious Disease Outbreaks(Research Data Alliance, 2020)How does data support preparedness towards infectious disease emergencies? What information is needed to identify the start of an outbreak? How does data inform the potential severity and spread of an outbreak? The infectious diseases data ecosystem is comprised of information from a wide range of sources like general practices, jurisdictional surveillance systems, clinical research, emergency departments, diagnostic laboratories, epidemiology studies and genomics. The carefully distilled knowledge from this diverse data ecosystem enables better preparedness for and response towards an outbreak. Past infectious disease outbreaks have demonstrated several challenges associated with rapid aggregation, integration and sharing of data to inform a response during an outbreak. It is essential to improve data collection, facilitate data sharing and support data usage for decision-making in the infectious diseases community. This keynote speech will describe the composition of the infectious disease data ecosystem and highlight some challenges from the past outbreaks associated with building the data ecosystem for a response. This speech will also describe how making data consistent and shareable has strengthened preparedness and response activities in present-day scenario.
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ItemDeveloping a workforce to support research reliant on data and compute(CEUR, 2021-01-01)We describe the construction, operation and evaluation of the Melbourne Data Analytics Platform; a group of academics whose mission is to support research requiring non-trivial data analysis or compute at the University of Melbourne.
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ItemValue of data aggregation to inform Australia's response to infectious disease emergencies(Public Health Association of Australia, 2019)Background: The infectious diseases data ecosystem is comprised of information from surveillance, clinical research, primary care, diagnostic laboratories, epidemiology and genomics. Past public health emergencies have demonstrated the challenges associated with rapid sharing of data to inform response. It is essential to improve data collection, facilitate data sharing and support data usage for decision-making in the communicable diseases community. Method: A literature review was undertaken to summarise existing practices in infectious diseases data management in Australia and internationally. The scoping work includes expert contributions from infectious diseases research, health informatics, bioinformatics and information systems. Results: Australia’s health and medical research strategic plans emphasise on enhanced data collection, efficient reporting systems and building advanced infrastructure. There is global support for making data available under F.A.I.R. (Findable, Accessible, Interoperable and Reusable) Principles to support knowledge integration, innovation and discovery. The Five Safes Framework (Projects, People, Data, Outputs and Settings) is an accountability framework to inform decisions about data usage. There are international exemplars of platforms that rapidly collect and disseminate data to inform public health responses. Ethically approved and harmonised protocols are essential tools for rapid collection, sharing and aggregation of data to support decision-making during an outbreak. Conclusion: The challenges in sharing and aggregating data can be addressed by building trust among data custodians, promoting collaboration and implementing data stewardship practices. The infrastructure solutions to leverage big data in infectious diseases should be agile, comply with ethical requirements and legislation, facilitate equitable data access and expedite cross-jurisdictional data sharing in Australia.
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ItemInformation Extraction from Legal Documents: A Study in the Context of Common Law Court Judgements(Australasian Language Technology Association, 2021)‘Common Law’ judicial systems follow the doctrine of precedent, which means the legal principles articulated in court judgements are binding in subsequent cases in lower courts. For this reason, lawyers must search prior judgements for the legal principles that are relevant to their case. The difficulty for those within the legal profession is that the information that they are looking for may be contained within a few paragraphs or sentences, but those few paragraphs may be buried within a hundred-page document. In this study, we create a schema based on the relevant information that legal professionals seek within judgements and perform text classification based on it, with the aim of not only assisting lawyers in researching cases, but eventually enabling large-scale analysis of legal judgements to find trends in court outcomes over time.
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