Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 77 tok/s
Gemini 2.5 Pro 45 tok/s Pro
GPT-5 Medium 30 tok/s Pro
GPT-5 High 28 tok/s Pro
GPT-4o 122 tok/s Pro
Kimi K2 178 tok/s Pro
GPT OSS 120B 450 tok/s Pro
Claude Sonnet 4.5 34 tok/s Pro
2000 character limit reached

Applications of Multi-Agent Slime Mould Computing (1511.05774v1)

Published 18 Nov 2015 in cs.ET

Abstract: The giant single-celled slime mould Physarum polycephalum has inspired rapid develop- ments in unconventional computing substrates since the start of this century. This is primarily due to its simple component parts and the distributed nature of the computation which it approximates during its growth, foraging and adaptation to a changing environment. Slime mould functions as a living embodied computational material which can be influenced (or pro- grammed) by the placement of external stimuli. The goal of exploiting this material behaviour for unconventional computation led to the development of a multi-agent approach to the ap- proximation of slime mould behaviour. The basis of the model is a simple dynamical pattern formation mechanism which exhibits self-organised formation and subsequent adaptation of collective transport networks. The system exhibits emergent properties such as relaxation and minimisation and it can be considered as a virtual computing material, influenced by the external application of spatial concentration gradients. In this paper we give an overview of this multi-agent approach to unconventional computing. We describe its computational mechanisms and different generic application domains, together with concrete example ap- plications of material computation. We examine the potential exploitation of the approach for computational geometry, path planning, combinatorial optimisation, data smoothing and statistical applications.

Citations (10)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Authors (1)

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Youtube Logo Streamline Icon: https://streamlinehq.com

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube