Modulating Interaction Times in an Artificial Society of Robots

Yara Khaluf*, Heiko Hamann

*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

In a collaborative society, sharing information is advantageous for each individual as well as for the whole community. Maximizing the number of agent-to-agent interactions per time becomes an appealing behavior due to fast information spreading that maximizes the overall amount of shared information. However, if malicious agents are part of society, then the risk of interacting with one of them increases with an increasing number of interactions. In this paper, we investigate the roles of interaction rates and times (aka edge life) in artificial societies of simulated robot swarms. We adapt their social networks to form proper trust sub-networks and to contain attackers. Instead of sophisticated algorithms to build and administrate trust networks, we focus on simple control algorithms that locally adapt interaction times by changing only the robots' motion patterns. We successfully validate these algorithms in collective decision-making showing improved time to convergence and energy-efficient motion patterns, besides impeding the spread of undesired opinions.

OriginalspracheEnglisch
Seiten372-379
Seitenumfang8
DOIs
PublikationsstatusVeröffentlicht - 07.2019
Veranstaltung2019 Conference on Artificial Life: How Can Artificial Life Help Solve Societal Challenges - Newcastle upon Tyne, Großbritannien / Vereinigtes Königreich
Dauer: 29.07.201902.08.2019
Konferenznummer: 159604

Tagung, Konferenz, Kongress

Tagung, Konferenz, Kongress2019 Conference on Artificial Life: How Can Artificial Life Help Solve Societal Challenges
KurztitelALIFE 2019
Land/GebietGroßbritannien / Vereinigtes Königreich
OrtNewcastle upon Tyne
Zeitraum29.07.1902.08.19

Fingerprint

Untersuchen Sie die Forschungsthemen von „Modulating Interaction Times in an Artificial Society of Robots“. Zusammen bilden sie einen einzigartigen Fingerprint.

Zitieren