2020 Expressions of Interest – call for Operations Research (OR) Collaboration
DST Group undertakes rigorous, scientifically based analysis of Defence operations and capabilities to provide independent, impartial and timely advice.
Our Mission is to develop and employ trusted analytical methods and decision support tools that give Defence and national security decision superiority across all aspects of force design, operational planning, command and control, and support to the Australian Defence Force on operations. DST Group and the state-based innovation networks are launching a call to academia to collaborate on a number of Defence OR topics through the Operations Research Network (ORnet).
The intention is that projects will run for a period of up to 10 months commencing in August 2020. Individual project proposals can indicate work up to $100K. There will be an expectation of an in-kind contribution in the successful proposal.
Submissions have now closed.
The ORnet is a collaborative initiative between Defence and academia that will bring together a network of universities to work on Defence problems. It was established to grow and strengthen the Australian operations research (OR) community’s ability to support Defence decision making, with a particular focus on Australian Defence Force design and employment. The intent of the ORnet is to provide coordinated pathways by which Defence can create enduring relationships between DST Group and academia to address challenging OR problems of national and strategic importance.
DST Group's Modelling Complex Warfighting (MCW) Strategic Research Investment (SRI) program is a five-year program which seeks to revolutionise how DST Group undertakes OR to better handle the interaction of complex geopolitical, social, technological, economic and cultural factors impacting the capability of the current force and design of the future force.
Topics of Interest
This call will be comprised of two components:
- MCW SRI topics
- General Defence OR topics.
Universities who are signatories to the Defence Science Partnerships (DSP) 2.0 program are welcome to submit proposals to any/all topics contained in this call, and the Commonwealth reserves the right to fund all or none of the topic areas.
MCW SRI Topics
1. Dynamic Planning under uncertainty for Autonomous Analyst
Within the Australian Defence Force, planning is a critical element to the success of campaigns and operations, as it enables the conversion of strategic objectives into a series of attainable military objectives. A 'plan' is a documental proposal to show how a decision may be undertaken such that an overarching intent can be achieved. The plan needs to consider all possible options and consequences that may occur, which is made even more difficult within an adversarial environment. This is why the planning process is critical, as it not only requires a detailed understanding of the intent, capabilities and actions, it also requires an understanding of the adversary's intent, capabilities and actions.
The development of an Autonomous Analyst refers to the need for analytically capable artificial intelligence (AI) where the machine has an ability (potentially of known limitation) to operate in environments manifesting uncertainty and ambiguity. To do this, AI must be carefully situated against a characterisation of the intended scenario that captures the mix of relative types of uncertainties and ambiguities involved; different factors important to decision-making may be long-term predictable, short-term predictable and irrevocably unpredictable.
The focus here is to develop a capability for machine planning and monitoring within an adversarial domain, where the actions of each participant are focussed on achieving their own intent, but also the goals and actions are dependent on beliefs about opponent intentions; where each other's beliefs and intents are not directly observable. Planning for, and operating, in this kind of environment is dynamic and complex, therefore once a plan is developed, there must be to ability to proactively monitor the goals against the plan, but also adapt the plan should the environment or situation change.
Understanding the bounds on uncertainty in the environment is the key to striking an ideal balance between consistency of behaviour over time and adaption (ideally pre-emptive) to changing conditions, which involves the exploration of courses of action and exploitation of opportunity and the consideration between efficiency and robustness under uncertainty. To demonstrate a potential capability, it is proposed that an idealised two / multi-player adversarial game (or framework) be developed. The overall intent of each player is identified (potentially not always the same), however the relevant goals are changeable and the participant's action is dependent on beliefs about adversary intentions may provide an exemplary platform for development, testing and demonstration of dynamic planning technology.
2. Influence and interference in the Grey Zone
Influence and interference are now central features of the contest spectrum (cooperation-competition-confrontation-conflict). The emergence of social media and other open source information confronts us with new opportunities and challenges in seeking to identify, respond to and measure the impact of influence and interference in the grey zone. Embracing a transdisciplinary approach is critical to further strengthening Defence’s ability to prevail in the grey zone.
This call seeks to bring together the social and behavioural sciences (SBS), operations analysis (OA) and management science (MS), and relevant Defence stakeholders to address the following two questions:
- How can we best combine models from a range of SBS disciplines, and at different levels of analysis (micro, meso and macro), to generate enhanced understanding of influence and interference?
- What are the ways that we can exploit this understanding to enhance the quality of multi-domain mission planning and force design through use of wargaming and related approaches?
The aim is to builds on the rich and diverse exploration of influence and interference undertaken by contributors to the Modelling Complex Human Systems theme in the first phase of the Modelling Complex Warfighting strategic research initiative. Out of this theme has also emerged a community of researchers committed to working across disciplinary boundaries. Through embracing OA/MS, and partnering with stakeholders and practitioners we seek to translate relevant SBS research into forms that deliver value to Defence planners and designers. As a result, proposals will ideally bring together researchers from these communities. Ideally researchers will also have experience working as part of transdisciplinary teams.
General Defence OR Topics
1. Comprehensive Simulation Meta-Modelling Capability
One of the key analytical activities in simulation analysis is the fitting of a white-box meta-model approximation to a black-box simulation. Fitting the meta-model requires (a) generation of input-output data based on a design of experiments; (b) a fit criterion that allows a best-fit meta-model to be determined; and (c) a means by which to statistically test the significance of the meta-model regression coefficients. For regression models associated with continuous, binary, or discrete simulation outputs, when independent-and-identically-distributed-residuals conditions cannot be assured, what is the optimal fit criterion; what is the optimal design of experiments; what is the correct statistical testing approach; and how can simulation output correlations or time-series data be exploited?
2. Defining new Metrics & Models for Land Conflict
Land conflict has and continues to undergo a transformation due to emerging technologies, evolving operating concepts and geo-political dimensions. Traditional metrics for operational effectiveness and mission success have focussed on the attrition of friendly and enemy forces, as well as subordinate measures such as shots on target. Given changes to land conflict these metrics appear limited in their ability to measure key aspects of modern conflict and could undermine the validity of related models to support modernisation and force design decision making in the future.
The goals for this activity are to define measures of tactical/operational effectiveness & mission success for modern land conflict, review existing mathematical modelling approaches and their underlying variables, including their interdependencies and propose alternative conceptual and mathematical representations of modern land conflict.
3. Intelligent Simulation Development Augmentation
Land Capability Analysis’s current closed loop simulation allows for deep analysis of specific scenarios. However, building these scenarios is currently very labour intensive, reducing the scope that can be considered within a given study. To allow for more robust analytical outcomes by covering a wider range of scenarios there is a need to bring more automation into the scenario development process. One approach that is currently being developed is applying machine learning techniques to decision making in support of the simulation development and execution. Any automation technique, machine learning or otherwise, needs to be open to analyst scrutiny, robust to variation and bounded by real world constraints. How can machine learning techniques be used to automate scenario development for combat simulations, how can the trained models be validated against real world constraints, and how can these models best be used to augment, rather than replace decision makers in the process?
Call for proposals
Interested Australian universities are encouraged to identify relevant fields of endeavour or expertise where they would be willing to engage and partner with DST Group. Universities are requested to submit proposals in response to the OR topic of interest. Proposals should outline research outcomes relevant to the topic(s), research methods, and relevant research experience and papers. Proposals should be a maximum of 2 pages.
The selected applicants will then be invited to virtual workshops, facilitated by DST Group, to develop a more detailed research program.
Where appropriate, there will be an opportunity to aggregate multiple proposals into multi-party agreements at a later time, up to a maximum total value of $200k. DST Group will continue to play a central role in this relationship, but academic organisations may also wish to form their own connections and propose multi-party research teams to DST Group.
Monday 15 June 2020 – Call for research collaboration proposals
Sunday 12 July 2020 – Closing date for research collaboration proposal submissions
From Monday 27 July 2020 – Selected partners are notified and invited to begin discussions on details of the collaboration
Monday 27 July to Wednesday 05 August 2020 – Discussions about work program requirements
Wednesday 05 August to Friday 22 August 2020 – Establishment and executions of collaborative research agreements
Friday 22 August 2020 to Wednesday 30 June 2021 – Duration of collaborative research agreements
Submitting Expressions of Interest: To submit an EOI for one of more research topics, please e-mail the required information to your relevant state-based innovation network.
|Applicant Location||Facilitation Network||Email Address|
|Victoria||Defence Science Institute (DSI)||ORNet-DSI@defencescienceinstitute.com|
|NSW||Defence Innovation Network (DIN)||firstname.lastname@example.org|
|South Australia||Defence Innovation Partnership (DIP)||email@example.com|
|Western Australia||Defence Science Centre (DSC)||firstname.lastname@example.org|
|Tasmania||Defence Science Institute (DSI)||ORNet-DSI@defencescienceinstitute.com|
|ACT||Defence Innovation Network (DIN)||email@example.com|
|Northern Territory||Defence Innovation Partnership (DIP)||firstname.lastname@example.org|
|Queensland||Defence Science Alliance (DSA)||email@example.com|