AIAI Seminar - 24/05/21 - Elliot Fosong & Rui Zhao

 

Speaker: Rui Zhao

 

 

Title: Dr.Aid: an automated formal framework to support data-governance rule compliance for decentralized collaboration

 

Abstract:

Collaboration across institutional boundaries is widespread and increasing today. It depends on federations sharing data that often have governance rules or external regulations restricting their use. However, the handling of data governance rules (aka. data-use policies) remains manual, time-consuming and error-prone, limiting the rate at which collaborations can form and respond to challenges and opportunities, inhibiting citizen science and reducing data providers' trust in compliance. Using an automated system to facilitate compliance handling reduces substantially the time needed for such non-mission work, thereby accelerating collaboration and improving productivity. We present a framework, Dr.Aid, that helps individuals, organisations and federations comply with data rules, using automation to track which rules are applicable as data is passed between processes and as derived data is generated. It encodes data-governance rules using a formal language and performs reasoning on multi-input-multi-output (MIMO) data-flow graphs in decentralised contexts. We test its power and utility by working with users performing cyclone tracking and earthquake modelling to support mitigation and emergency response. We query standard provenance traces to detach Dr.Aid from details of the tools and systems they are using, as these inevitably vary across members of a federation and through time. We evaluate the model by encoding real-life data-use policies from diverse fields, showing its capability. We argue that this approach will lead to more agile, more productive and more trustworthy collaborations and show that the approach can be adopted incrementally. This, in-turn, will allow more appropriate data policies to emerge, opening up new forms of collaboration.

 

 

Speaker: Elliot Fosong

 

Title: Exploratory probing and the game of Hanabi

 

Abstract:

In many domains, it may be desirable to design autonomous agents which are able to build accurate behavioural models of other agents from limited interactions with those agents. Agents could take exploratory probing actions with the intention of intelligently eliciting information that improves the accuracy of the agent's model of others. Devising strategies which can probe efficiently and safely whilst balancing exploration and exploitation remains a key challenge. In this talk, we discuss the co-operative multiplayer card game Hanabi. We discuss how Hanabi may provide a suitable test-bed for research into exploratory probing in multi-agent systems. We provide an overview of various relevant approaches taken so far, identify remaining challenges in to Hanabi-playing agents, and some initial ideas for addressing those challenges.

 

 

 

 

May 24 2021 -

AIAI Seminar - 24/05/21 - Elliot Fosong & Rui Zhao

AIAI Seminar talk hosted by Elliot Fosong & Rui Zhao

Online