[HTML][HTML] Coalition structure generation: A survey
The coalition structure generation problem is a natural abstraction of one of the most
important challenges in multi-agent systems: How can a number of agents divide …
important challenges in multi-agent systems: How can a number of agents divide …
Data shapley: Equitable valuation of data for machine learning
A Ghorbani, J Zou - International conference on machine …, 2019 - proceedings.mlr.press
As data becomes the fuel driving technological and economic growth, a fundamental
challenge is how to quantify the value of data in algorithmic predictions and decisions. For …
challenge is how to quantify the value of data in algorithmic predictions and decisions. For …
Counterfactuals and causability in explainable artificial intelligence: Theory, algorithms, and applications
Deep learning models have achieved high performance across different domains, such as
medical decision-making, autonomous vehicles, decision support systems, among many …
medical decision-making, autonomous vehicles, decision support systems, among many …
Algorithmic transparency via quantitative input influence: Theory and experiments with learning systems
Algorithmic systems that employ machine learning play an increasing role in making
substantive decisions in modern society, ranging from online personalization to insurance …
substantive decisions in modern society, ranging from online personalization to insurance …
Machine learning in network centrality measures: Tutorial and outlook
Complex networks are ubiquitous to several computer science domains. Centrality
measures are an important analysis mechanism to uncover vital elements of complex …
measures are an important analysis mechanism to uncover vital elements of complex …
Efficient task-specific data valuation for nearest neighbor algorithms
Given a data set $\mathcal {D} $ containing millions of data points and a data consumer who
is willing to pay for\$$ X $ to train a machine learning (ML) model over $\mathcal {D} $, how …
is willing to pay for\$$ X $ to train a machine learning (ML) model over $\mathcal {D} $, how …
Centrality measures in networks
We show that prominent centrality measures in network analysis are all based on additively
separable and linear treatments of statistics that capture a node's position in the network …
separable and linear treatments of statistics that capture a node's position in the network …
Optimal sizing of energy communities with fair revenue sharing and exit clauses: Value, role and business model of aggregators and users
Energy communities (ECs) are essential tools to meet the Energy Transition goals but, to
fully unleash their potential, they require a coordinated operation and design that the …
fully unleash their potential, they require a coordinated operation and design that the …
Human-agent collectives
NR Jennings, L Moreau, D Nicholson… - Communications of the …, 2014 - dl.acm.org
Human-agent collectives Page 1 80 COMMUNICATIONS OF THE ACM | DECEMBER 2014 |
VOL. 57 | NO. 12 review articles DOI:10.1145/2629559 HACs offer a new science for exploring …
VOL. 57 | NO. 12 review articles DOI:10.1145/2629559 HACs offer a new science for exploring …
Shapley Q-value: A local reward approach to solve global reward games
Cooperative game is a critical research area in the multi-agent reinforcement learning
(MARL). Global reward game is a subclass of cooperative games, where all agents aim to …
(MARL). Global reward game is a subclass of cooperative games, where all agents aim to …