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Sarah Hickmott
Researcher at RMIT University
Publications - 12
Citations - 252
Sarah Hickmott is an academic researcher from RMIT University. The author has contributed to research in topics: Sustainability reporting & Sustainability. The author has an hindex of 5, co-authored 11 publications receiving 222 citations.
Papers
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Journal ArticleDOI
Reframing social sustainability reporting: towards an engaged approach
Liam Magee,Andy Scerri,Paul James,James A. Thom,Lin Padgham,Sarah Hickmott,Hepu Deng,Felicity Cahill +7 more
TL;DR: In this paper, the authors outline a methodology for framing sustainability assessment and developing indicator sets that aim to bridge the gap between top-down and bottom-up approaches to sustainability assessment.
Proceedings ArticleDOI
An architecture for modular distributed simulation with agent-based models
TL;DR: This paper describes a framework and architecture which facilitates the integration of multiple agent-based simulations into a single global simulation and naturally supports distributed simulation and incremental development, which are ways of addressing the computational and conceptual complexity of such systems.
Proceedings ArticleDOI
Integrating BDI reasoning into agent based modeling and simulation
TL;DR: This work takes a Belief Desire Intention (BDI) agent platform and embeds it into Repast, to support more powerful modeling of human behavior.
Journal Article
Using modular simulation and agent based modelling to explore emergency management scenarios
TL;DR: Two emerging simulation technologies, Agent Based Modelling and Modular simulation development, are presented and it is described how they could aid with communication, collaboration and understanding of complex emergency management scenarios.
Proceedings Article
Optimality properties of planning via Petri net unfolding: a formal analysis
Sarah Hickmott,Sebastian Sardina +1 more
TL;DR: This paper formally characterise the concurrency semantics of planning via unfolding as a further restriction on the standard notion of independence and proves that plans obtained using this approach are optimal deorderings and optimal reorderings in terms of the number of ordering constraints on operators and plan execution time, respectively.