Вход на сайт

Просмотр новости

Найдите то, что Вас интересует

Resource Allocation with Multi-Team Collaboration Based on Hamilton’s Rule

Дата публикации: 27-08-2026 00:00:00

This paper presents a multi-team collaboration strategy based on Hamilton’s rule from ecology that facilitates resource allocation among multiple teams, where agents are considered as shared resource among all teams that must be allocated appropriately. We construct an algorithmic framework that allows teams to make bids for agents that consider the costs and benefits of transferring agents while also considering relative mission importance for each team. This framework is applied to a multi-team coverage control mission to demonstrate its effectiveness. It is shown that the necessary criteria of a mission evaluation function are met by framing it as a function of the locational coverage cost of each team with respect to agent gain and loss, and these results are illustrated through simulations.

Схожие новости

#Наименование новостиТональностьИнформативностьДата публикации
1District Heterogeneity, Legislative Bargaining, and Trade Policy05.4106-03-2026
2Integrating experimental and observational approaches facilitates scaling species interactions to biodiversity patterns06.714-08-2026
3Review of Hybrid Localization Frameworks in Wireless Sensor Networks for Precision Agriculture Applications [version 1; peer review: awaiting peer review]09.5924-07-2026
4Basking in the Warmth of the Red Queen: Novel Methods for Studying Rattlesnake Behavioral Strategies with Agent-Based Models011.7720-07-2026
5The Ensemble Learning to Determine Optimal Tuning Parameter of the Generalized Lasso in Spatial Clustering Analysis05.122-07-2026
6A Hierarchical Hydro-Economic Modeling Framework for Policy Support and Impact Assessment: the case of a highly anthropized Mediterranean Semi-Arid Alpine Basin0517-07-2026
7Remote Sensing for Forest Monitoring Across Four and a Half Decades: Mapping Knowledge Evolution, Scientific Collaboration, and Emerging Research Frontiers [version 2; peer review: awaiting peer review]0818-08-2026
8Technology Adoption and Optimal Policy06.8208-05-2026
9 Contrasting Local and Global Modeling with Machine Learning and Satellite Data: A Case Study Estimating Tree Canopy Height in African Savannas 05.6817-08-2026
10Deep learning-based computer vision in forest monitoring and management: a systematic review0806-07-2026

Классификация: . Схожих патентов: 0. Схожих новостей: 10. Тональность: 0. Информативность: 6.83. Источник: escholarship.org.