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Computer Science > Neural and Evolutionary Computing

arXiv:2203.06855 (cs)
[Submitted on 14 Mar 2022 (v1), last revised 3 May 2022 (this version, v2)]

Title:DIAS: A Domain-Independent Alife-Based Problem-Solving System

Authors:Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen
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Abstract:A domain-independent problem-solving system based on principles of Artificial Life is introduced. In this system, DIAS, the input and output dimensions of the domain are laid out in a spatial medium. A population of actors, each seeing only part of this medium, solves problems collectively in it. The process is independent of the domain and can be implemented through different kinds of actors. Through a set of experiments on various problem domains, DIAS is shown able to solve problems with different dimensionality and complexity, to require no hyperparameter tuning for new problems, and to exhibit lifelong learning, i.e. adapt rapidly to run-time changes in the problem domain, and do it better than a standard non-collective approach. DIAS therefore demonstrates a role for Alife in building scalable, general, and adaptive problem-solving systems.
Comments: 9 pages, 6 figures
Subjects: Neural and Evolutionary Computing (cs.NE); Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Multiagent Systems (cs.MA)
Cite as: arXiv:2203.06855 [cs.NE]
  (or arXiv:2203.06855v2 [cs.NE] for this version)
  https://doi.org/10.48550/arXiv.2203.06855
Journal reference: Proceedings of the 2022 Conference on Artificial Life

Submission history

From: Risto Miikkulainen [view email]
[v1] Mon, 14 Mar 2022 04:53:26 UTC (321 KB)
[v2] Tue, 3 May 2022 23:12:08 UTC (365 KB)
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