A biologically-inspired platform for the evolution of communication in multi-agent systems

被引:0
|
作者
McKennoch, S [1 ]
McNew, JM [1 ]
Bushnell, LG [1 ]
机构
[1] Univ Washington, Dept Elect Engn, Seattle, WA 98195 USA
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This research effort seeks to address the problem of limited communication in multi-agent systems by the use biologically-inspired implementations of intelligent control systems. A detailed simulation platform is built and tested. The platform contains many user-configurable parameters and is intended to be used as a general purpose research tool for the study of the evolution of communication in multi-agent systems. The user-configurable parameters include those that modify the agent environment, the structure of agent communication abilities, and various simulated biological selection forces and influences including natural selection, cultural transmission, and sexual selection. The simulation involves a predator-prey (pursuer-evader) environment in which evolving predators seek to capture prey and thus increase their fitness. Agents are given the ability to communicate, but are not forced to do so. Simulation results are presented to demonstrate the usefulness and abilities of this tool.
引用
收藏
页码:719 / 726
页数:8
相关论文
共 50 条
  • [1] A Biologically-Inspired Multi-Agent Framework for Autonomic Service Management
    Chiang, Frank
    Braun, Robin
    Hughes, John
    [J]. INTERNATIONAL JOURNAL OF PERVASIVE COMPUTING AND COMMUNICATIONS, 2007, 2 (03) : 261 - +
  • [2] Biologically-Inspired Control for Multi-Agent Self-Adaptive Tasks
    Yu, Chih-Han
    Nagpal, Radhika
    [J]. PROCEEDINGS OF THE TWENTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI-10), 2010, : 1702 - 1707
  • [3] A biologically-inspired algorithm implemented on a new highly flexible multi-agent platform for gas source localization
    Ferri, Gabriele
    Caselli, Emanuele
    Mattoli, Virgilio
    Mondini, Alessio
    Mazzolai, Barbara
    Dario, Paolo
    [J]. 2006 1ST IEEE RAS-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL ROBOTICS AND BIOMECHATRONICS, VOLS 1-3, 2006, : 182 - +
  • [4] A Study on Some Aspects of Biologically Inspired Multi-agent Systems
    Mitra, Gautam
    Bandyopadhyay, Susmita
    [J]. PROGRESS IN ADVANCED COMPUTING AND INTELLIGENT ENGINEERING, VOL 2, 2018, 564 : 207 - 217
  • [5] BATS VERSUS BUGS: COLLECTIVE BEHAVIOR OF PREY DECREASES PREDATION IN A BIOLOGICALLY-INSPIRED MULTI-AGENT SYSTEM
    Lin, Yuan
    Abaid, Nicole
    [J]. PROCEEDINGS OF THE ASME 2013 DYNAMIC SYSTEMS AND CONTROL CONFERENCE (DSCC2013), VOL. 1, 2013,
  • [6] A Biologically-Inspired Distributed Resilient Flocking Control for Multi-Agent System with Uncertain Dynamics and Unknown Disturbances
    Jafari, Mohammad
    Xu, Hao
    [J]. 2017 RESILIENCE WEEK (RWS), 2017, : 71 - 76
  • [7] TrustMAS: Trusted Communication Platform for Multi-Agent Systems
    Szczypiorski, Krzysztof
    Margasinski, Igor
    Mazurczyk, Wojciech
    Cabaj, Krzysztof
    Radziszewski, Pawel
    [J]. ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS: OTM 2008, PT II, PROCEEDINGS, 2008, 5332 : 1019 - 1035
  • [8] Biologically-inspired radar and sonar systems
    Leighton, T. G.
    Balleri, A.
    [J]. IET RADAR SONAR AND NAVIGATION, 2012, 6 (06): : 507 - 509
  • [9] A biologically-inspired reinforcement learning based intelligent distributed flocking control for Multi-Agent Systems in presence of uncertain system and dynamic environment
    Jafari, Mohammad
    Xu, Hao
    Carrillo, Luis Rodolfo Garcia
    [J]. IFAC JOURNAL OF SYSTEMS AND CONTROL, 2020, 13
  • [10] Communication by identity discrimination in bio-inspired multi-agent systems
    Gonzalez-Pardo, Antonio
    Varona, Pablo
    Camacho, David
    Rodriguez Ortiz, Francisco de Borja
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2012, 24 (06): : 589 - 603