A New Method for Improving the Fairness of Multi|Robot Task ...

A New Method for Improving the Fairness of Multi-Robot Task ...

The method provides a more adaptable and flexible solution than traditional algorithms, which might not be able to adequately address these variations because ...

(PDF) A New Method for Improving the Fairness of Multi-Robot Task ...

Abstract and Figures · 1: Perform initialization. · 2: All numbers in each row are subtracted from the row's. minimum number. · 3: Based on the ...

[PDF] A New Method for Improving the Fairness of Multi-Robot Task ...

The proposed method takes a comprehensive approach to initialization by integrating the K-means clustering algorithm, the Hungarian method for solving the ...

A New Method for Improving the Fairness of Multi-Robot Task ...

This paper presents an innovative task allocation method for multi-robot systems that aims to optimize task distribution while taking into account various ...

Msala | Journal of Robotics and Control (JRC)

A New Method for Improving the Fairness of Multi-Robot Task Allocation by Balancing the Distribution of Tasks.

[2402.15638] Fair Resource Allocation in Multi-Task Learning - arXiv

Extensive experiments demonstrate that our method can achieve state-of-the-art performance among gradient manipulation methods on a suite of ...

Consensus-based fast and energy-efficient multi-robot task allocation

Predominantly, decentralized task allocation methods follow various bidding-based schemes. Given a set of tasks, a robot can derive a bid value indicating its ...

Understanding and Improving Fairness-Accuracy Trade-offs in Multi ...

propose a Multi-Task-Aware Fairness (MTA-F) approach to improve fairness in multi-task learning. Experiments on several real-world datasets demonstrate the ...

(PDF) A Machine Learning Method for Improving Task Allocation in ...

robots modeled. ... capabilities needed to specify the eﬀects of interaction on group performance. ... too many simplifying assumptions to be of predictive use.

Rethinking Fairness Representation in Multi-Task Learning

However, task imbalance remains a major challenge for existing MTL methods. While the prior works have attempted to mitigate inter-task ...

Multi‐station multi‐robot task assignment method based on deep ...

As a result, the search space for the solution is reduced by segmenting the large-scale optimisation problem. In order to reduce gradient ...

FairBranch: Mitigating Bias Transfer in Fair Multi-task Learning - arXiv

Fair-MTL methods try to optimize for both accuracy and fairness [6, 7, 5] , by incorporating, for example, a fairness loss alongside the ...

Optimization techniques for Multi-Robot Task Allocation problems

It is generally modeled using methods from operations research, that makes use of mathematical models to improve complex systems. It is a wide ...

Fairness in Multi-Task Learning via Wasserstein Barycenters ...

Our approach provides a closed form solution for the optimal fair multi-task predictor including both regression and binary classification tasks. We develop a ...

A new Robust Heterogeneous Multi-Robot Approach Based on ...

A conceptual architecture is presented, that ensures coordination between the entire team of heterogeneous robots and then a new strategy based on ...

Papers with Code - Transferring Fairness using Multi-Task Learning ...

Training supervised machine learning systems with a fairness loss can improve prediction fairness across different demographic groups.

Multi-objective task allocation for collaborative robot systems with an ...

[29] primarily focused on enhancing efficiency in human-robot collaboration (HRC) by utilizing group control methods and algorithms to create a ...

FERI: A Multitask-based Fairness Achieving Algorithm with ... - NCBI

Methodological Innovation: Within a multitask learning framework, we propose a FERI algorithm to balance the subgroup training process through ...

Understanding and Improving Fairness-Accuracy Trade-offs in Multi ...

We propose a new set of metrics to better capture the multi ... We further propose a Multi-Task-Aware Fairness (MTA-F) approach to improve fairness in multi-task ...

Proactive Multi-Robot Task Allocation Under Spatiotemporal ...

To adapt SSI for online deployments, new tasks are inserted into a robot's existing schedule (Schoenig & Pagnucco, 2010). To improve allocations, Zheng et al. ( ...