Jove
Visualize
联系我们

相关概念视频

Predator-Prey Interactions02:39

Predator-Prey Interactions

16.1K
Predators consume prey for energy. Predators that acquire prey and prey that avoid predation both increase their chances of survival and reproduction (i.e., fitness). Routine predator-prey interactions elicit mutual adaptations that improve predator offenses, such as claws, teeth, and speed, as well as prey defenses, including crypsis, aposematism, and mimicry. Thus, predator-prey interactions resemble an evolutionary arms race.
16.1K
Communication01:03

Communication

7.7K
Communication between two animals occurs when one animal transmits an information signal that causes a change in the animal that receives the information. Organisms communicate with one another in a host of different ways. Signals can be auditory, chemical, visual, tactile, or a combination of these. Communication is a critical behavioral adaptation that promotes survival, growth, and reproduction.
7.7K
Production Efficiency01:01

Production Efficiency

16.7K
Net production efficiency (NPE) is the efficiency at which organisms assimilate energy into biomass for the next trophic level. Due to low metabolic rates and less energy spent on thermoregulatory processes, the NPE of ectotherms (cold-blooded animals) is 10 times higher than endotherms (warm-blooded animals).
16.7K
Trophic Efficiency00:46

Trophic Efficiency

20.3K
Trophic level transfer efficiency (TLTE) is a measure of the total energy transfer from one trophic level to the next. Due to extensive energy loss as metabolic heat, an average of only 10% of the original energy obtained is passed on to the next level. This pattern of energy loss severely limits the possible number of trophic levels in a food chain.
20.3K
Inclusive Fitness00:57

Inclusive Fitness

35.9K
Most altruistic behavior—in which one animal helps another at a cost to themselves—occurs between relatives. Scientists think these altruistic behaviors evolved because they increase the inclusive fitness of the animal providing help.
35.9K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Swarms can be rational.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2025
Same author

The visual stimuli attributes instrumental for collective-motion-related decision-making in locusts.

PNAS nexus·2024
Same author

Vision-based collective motion: A locust-inspired reductionist model.

PLoS computational biology·2024
Same author

The hybrid bio-robotic swarm as a powerful tool for collective motion research: a perspective.

Frontiers in neurorobotics·2023
Same author

Towards Computational Modeling of Human Goal Recognition.

Frontiers in artificial intelligence·2022
Same author

Molecular Robots Obeying Asimov's Three Laws of Robotics.

Artificial life·2017
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: May 29, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.3K

不同质的食群可能更好.

Gal A Kaminka1, Yinon Douchan1

  • 1Department of Computer Science, Gonda Brain Research Center, and Nanotechnology Center, Bar Ilan University, Ramat Gan, Israel.

Frontiers in robotics and AI
|February 4, 2025
PubMed
概括

这项研究表明,异构的机器人群通过调整行为角色来提高性能. 一个新的奖励功能,Aligned Effective Index,将个人机器人的目标与群体目标对齐,以实现更好的协调.

科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 人工智能的人工智能
  • 游戏理论 游戏理论

背景情况:

  • 群体机器人研究专注于在有限的个人感知和沟通的情况下实现连贯的集体行为.
  • 之前的方法使用了分布式强化学习与有效性指数 (EI) 奖励,这可能导致由于自私优化导致群体性能下降.

研究的目的:

  • 为群体机器人开发一种新的奖励功能,以改善协调和性能.
  • 解决分散的群体系统中的有效性指数 (EI) 的局限性.
  • 为了证明在群体优化中异质行为角色的好处.

主要方法:

  • 模拟群体食作为一个完全合作的,重复的游戏.
  • 从游戏理论的角度来看,利用边际贡献推导出了一个新的奖励函数,即对准有效指数 (AEI).
  • 分析了协调空头和小群实用之间的关系.
  • 将机器人缺席的反事实分析纳入奖励函数.

主要成果:

  • 结合有效指数 (AEI) 奖励函数将个人机器人的决策与群体范围内的目标结合起来.
  • AEI可被证明是对以前的方法进行了概括,并解释了个人行动对集体的影响.
  • 使用模拟机器人和真实机器人的实验验证了AEI的有效性,并强调了行为多样性的重要性.
关键词:
不同的差异,奖励的奖励.寻找料,寻找食物,寻找其他食物.游戏理论的游戏理论.不同质的机器人 不同质的机器人这是一个边际贡献.多种代理强化学习的多种代理强化学习机器人多样性 机器人多样性群众机器人工程 群众机器人工程

更多相关视频

Obtaining Specimens with Slowed, Accelerated and Reversed Aging in the Honey Bee Model
10:58

Obtaining Specimens with Slowed, Accelerated and Reversed Aging in the Honey Bee Model

Published on: August 29, 2013

11.2K
A Push-pull Protocol to Reduce Colonization of Bird Nest Boxes by Honey Bees
06:03

A Push-pull Protocol to Reduce Colonization of Bird Nest Boxes by Honey Bees

Published on: September 4, 2016

8.6K

相关实验视频

Last Updated: May 29, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.3K
Obtaining Specimens with Slowed, Accelerated and Reversed Aging in the Honey Bee Model
10:58

Obtaining Specimens with Slowed, Accelerated and Reversed Aging in the Honey Bee Model

Published on: August 29, 2013

11.2K
A Push-pull Protocol to Reduce Colonization of Bird Nest Boxes by Honey Bees
06:03

A Push-pull Protocol to Reduce Colonization of Bird Nest Boxes by Honey Bees

Published on: September 4, 2016

8.6K

结论:

  • 拟议的对齐有效指数 (AEI) 奖励函数可以提高群体协调和性能.
  • 异质的行为角色对于优化群体目标至关重要.
  • 理论框架和经验验证证明了群体机器人的实际进步.