Bio-Inspired Approaches in Artificial Intelligence: Innovations in Machine Learning and Multi-Agent Systems

Dear Colleagues,

Introduction

Artificial Intelligence (AI) has been significantly influenced by biological systems, leading to innovative and robust methodologies that mimic natural processes. Bio-inspired AI leverages principles from biological evolution, neural mechanisms, swarm intelligence, and ecological interactions to develop more adaptive and scalable learning algorithms. As machine learning and multi-agent systems continue to evolve, bio-inspired approaches provide promising solutions to enhance intelligence, efficiency, and autonomy in AI applications.

We are pleased to invite researchers and experts to contribute to this Special Issue, which will focus on the latest advancements in bio-inspired machine learning and multi-agent systems. We encourage high-quality submissions that present theoretical developments, empirical studies, and real-world applications in this rapidly growing field.

Aim and Scope

This Special Issue aims to bring together cutting-edge research on bio-inspired artificial intelligence, particularly in the domains of machine learning and multi-agent systems. It seeks to highlight novel methodologies, applications, and interdisciplinary approaches that bridge the gap between biological principles and artificial systems. The scope of this Special Issue aligns with the journal’s focus on AI innovations, computational intelligence, and autonomous decision-making frameworks.

Suggested Themes and Article Types

We welcome original research articles and review papers covering, but not limited to, the following topics:

• Evolutionary algorithms and optimization techniques in AI;
• Neural and cognitive-inspired learning architectures;
• Swarm intelligence and collective decision-making in multi-agent systems;
• Bio-inspired reinforcement learning;
• Artificial immune systems and anomaly detection;
• Genetic programming for adaptive AI solutions;
• Applications of bio-inspired AI;
• Nature-inspired computing frameworks for distributed and autonomous systems;
• Self-organizing and adaptive multi-agent coordination;
• Theoretical and empirical insights into bio-inspired AI methodologies;
• Agentic AI and applications.

We look forward to your valuable contributions.

Prof. Dr. Elhadj Benkhelifa
Prof. Dr. Brij B. Gupta
Prof. Dr. Tamara Zhukabayeva
Prof. Dr. Chirine Ghedira Guegan
Prof. Dr. Nadia Kabachi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.