NDLI: Decentralised and Adaptive Collaboration in Multi-agent Systems

Content Provider	IEEE Xplore Digital Library
Author	Çakar, E. Müller-Schloer, C.
Copyright Year	2010
Abstract	Developing multi-agent systems with self-interested agents with a large behavioural repertoire is a great challenge. In this paper, we pursue the question of how to combine collaborative and non-collaborative agent behaviours in a way to outperform each behaviour individually. In this context, we investigate different collaboration patterns between the agents in a test scenario from the predator-prey domain. Here, the predators move around a 2-D grid and use a parameterisable behaviour model to determine their positions on the grid. Having this behaviour model, each predator can modify a single parameter to change/adapt its behaviour against other predators in the system. This adaptation can be done either (1) in a collaborative way, where the predators collectively search for the optimal set of parameters on behalf of the whole group or (2) in a non-collaborative way, where each predator changes its behaviour individually only on its own behalf. We investigate a method for adaptively combining these behaviours and show how to quantify the resulting behaviour.
Starting Page	195
Ending Page	202
File Size	388960
Page Count	8
File Format	PDF
ISBN	9781424476022
e-ISBN	9781424476015
DOI	10.1109/ISPDC.2010.24
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-07
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multiagent systems Collaborative work System performance Testing Systems engineering and theory Self-assembly Distributed computing International collaboration Orbital robotics Mobile robots Collaboration Multi-agent systems Bio-inspired algorithms
Content Type	Text
Resource Type	Article

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