Behavioral model summarisation for other agents under uncertainty

Pan, Yinghui; Ma, Biyang; Tang, Jing; Zeng, Yanjun

doi:10.1016/j.ins.2021.09.039

Cited by 7 publications

(8 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the study lights up critical thoughts about behavior diversity and its impact on a subject agent's decision quality. Thoughts are also captured by the recent I-DID study although the work still focuses on known behaviors of other agents [29]. Hence, this work will open a new field on developing I-DID solutions based on diversifying other agents' behaviors.…”

Section: Multiagent Uav Problemsmentioning

confidence: 97%

“…The reduction differs from the previous work on reducing agent j 's behavior space since it is to find representative behavior patterns and does not aim to compress the behavior space [7,28,29].…”

Section: Agent J's Possible Modelsmentioning

confidence: 99%

“…The features could reflect representative patterns of what the other agent acts given its beliefs about the environment. The reduction differs from the previous work on reducing agent

j

's behavior space since it is to find representative behavior patterns and does not aim to compress the behavior space 7,27,28 …”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Diversifying agent's behaviors in interactive decision models

Pan

Zhang

Zeng

et al. 2022

Int J of Intelligent Sys

Self Cite

View full text Add to dashboard Cite

Section: Multiagent Uav Problemsmentioning

confidence: 97%

Section: Agent J's Possible Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Diversifying agent's behaviors in interactive decision models

Pan

Zhang

Zeng

et al. 2022

Int J of Intelligent Sys

Self Cite

View full text Add to dashboard Cite

Section: Agent J's Possible Modelsmentioning

confidence: 99%

“…quality. Thoughts are also captured by the recent I-DID study although the work still focuses on known behaviors of other agents[10]. Hence, this work will open a new field on developing I-DID solutions based on diversifying other agents' behaviors.…”

mentioning

confidence: 97%

Diversifying Agent's Behaviors in Interactive Decision Models

Pan¹,

Zhang²,

Zeng³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

The soft underbelly of complexity science adoption in policymaking: towards addressing frequently overlooked non-technical challenges

Nel,

Taeihagh

2024

Policy Sci

View full text Add to dashboard Cite

The deepening integration of social-technical systems creates immensely complex environments, creating increasingly uncertain and unpredictable circumstances. Given this context, policymakers have been encouraged to draw on complexity science-informed approaches in policymaking to help grapple with and manage the mounting complexity of the world. For nearly eighty years, complexity-informed approaches have been promising to change how our complex systems are understood and managed, ultimately assisting in better policymaking. Despite the potential of complexity science, in practice, its use often remains limited to a few specialised domains and has not become part and parcel of the mainstream policy debate. To understand why this might be the case, we question why complexity science remains nascent and not integrated into the core of policymaking. Specifically, we ask what the non-technical challenges and barriers are preventing the adoption of complexity science into policymaking. To address this question, we conducted an extensive literature review. We collected the scattered fragments of text that discussed the non-technical challenges related to the use of complexity science in policymaking and stitched these fragments into a structured framework by synthesising our findings. Our framework consists of three thematic groupings of the non-technical challenges: (a) management, cost, and adoption challenges; (b) limited trust, communication, and acceptance; and (c) ethical barriers. For each broad challenge identified, we propose a mitigation strategy to facilitate the adoption of complexity science into policymaking. We conclude with a call for action to integrate complexity science into policymaking further.

show abstract

Behavioral model summarisation for other agents under uncertainty

Cited by 7 publications

References 20 publications

Diversifying agent's behaviors in interactive decision models

Diversifying agent's behaviors in interactive decision models

Diversifying Agent's Behaviors in Interactive Decision Models

The soft underbelly of complexity science adoption in policymaking: towards addressing frequently overlooked non-technical challenges

Contact Info

Product

Resources

About