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Grant: Discovery Grants Program - Individual

University of Waterloo

$96,000.00

Decision Making in Heterogenous Multiagent Systems

FY 2022-23

Summary
The recently released ``One Hundred Year Study on Artificial Intelligence" emphasized the importance of developing human-aware systems, that are explicitly designed taking into consideration the fact that humans are an integral part. For example, one can envision autonomous systems that seamlessly interact with humans, leveraging the strengths of both computational agents and humans as required, augmenting the abilities of both. However, in order for such systems to be realized, there are numerous research challenges which need to be addressed, ranging from the design of interfaces to support human-machine collaboration to formal models of effective interaction.One central challenge is ensuring that preferences and incentives of both humans and the agents representing them are appropriately aligned, as misunderstandings and misalignment of incentives can lead to unexpected outcomes and undesirable behaviour. Furthermore, systems must be explicitly designed so as to ensure robust and transparent outcomes, respecting the agents' (both human and computational) preferences and values. In this proposal I describe a research agenda that, by developing and levering research in algorithmic game theory, computational social choice and, more broadly, multiagent systems and artificial intelligence, will support the development of robust human-aware systems.The impact of this research will be felt across multiple dimensions. First, it will address fundamental questions in multiagent systems and artificial intelligence. Progress in this area will support the development of robust multiagent systems that can used across a wide range of application domains. Finally, central to the proposal is the training of highly qualified personnel in artificial intelligence, an area where there is strong national demand across all industries and sectors.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2018-03962
Name nom
Larson, Kate
Department département
Computer Science, David R. Cheriton School of - Computer Science, David R. Cheriton School of
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2018
Award amount
96000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
800
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information and communication services
Area of application fr
Services d'information et de télécommunications
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Artificial intelligence (computer vision, use2603)
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Installment
inst:5;6
Partie
2
Nb partie
6
Application title
Decision Making in Heterogenous Multiagent Systems
Application summary
The recently released ``One Hundred Year Study on Artificial Intelligence" emphasized the importance of developing human-aware systems, that are explicitly designed taking into consideration the fact that humans are an integral part. For example, one can envision autonomous systems that seamlessly interact with humans, leveraging the strengths of both computational agents and humans as required, augmenting the abilities of both. However, in order for such systems to be realized, there are numerous research challenges which need to be addressed, ranging from the design of interfaces to support human-machine collaboration to formal models of effective interaction.One central challenge is ensuring that preferences and incentives of both humans and the agents representing them are appropriately aligned, as misunderstandings and misalignment of incentives can lead to unexpected outcomes and undesirable behaviour. Furthermore, systems must be explicitly designed so as to ensure robust and transparent outcomes, respecting the agents' (both human and computational) preferences and values. In this proposal I describe a research agenda that, by developing and levering research in algorithmic game theory, computational social choice and, more broadly, multiagent systems and artificial intelligence, will support the development of robust human-aware systems.The impact of this research will be felt across multiple dimensions. First, it will address fundamental questions in multiagent systems and artificial intelligence. Progress in this area will support the development of robust multiagent systems that can used across a wide range of application domains. Finally, central to the proposal is the training of highly qualified personnel in artificial intelligence, an area where there is strong national demand across all industries and sectors.
University of Waterloo - $96,000 Grant (2022-23) | Canada Spends