Naslov
The impact of agent definitions and interactions on multiagent learning for coordination in traffic management domains

Autori
Chung, Jen Jen ; Miklić, Damjan ; Sabattini, Lorenzo ; Tumer, Kagan ; Siegwart, Roland

Izvornik
Autonomous Agents and Multi-Agent Systems (1387-2532) 34 (2020), 1; 21, 29

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
multiagent systems ; learning ; coordination ; traffic management

Sažetak
The state-action space of an individual agent in a multiagent team fundamentally dictates how the individual interacts with the rest of the team. Thus, how an agent is defined in the context of its domain has a significant effect on team performance when learning to coordinate. In this work we explore the trade-offs associated with these design choices, for example, having fewer agents in the team that individually are able to process and act on a wider scope of information about the world versus a larger team of agents where each agent observes and acts in a more local region of the domain. We focus our study on a traffic management domain and highlight the trends in learning performance when applying different agent definitions. In addition, we analyze the impact of agent failure for different agent definitions and investigate the ability of the team to learn new coordination strategies when individual agents become unresponsive.

Izvorni jezik
Engleski

Znanstvena područja
Interdisciplinarne tehničke znanosti

POVEZANOST RADA