مخطط الموضوع
عام
Course presentation
This course introduces students to the fundamental concepts of bio-inspired computing, exploring how natural systems such as evolution, swarm behavior, and the immune response can inspire innovative computational methods. It highlights key approaches including evolutionary algorithms, swarm intelligence techniques, and artificial immune systems. Through these nature-inspired paradigms, students learn how to design adaptive, robust, and efficient solutions to complex computational problems. The course also emphasizes practical applications across optimization, machine learning, and problem-solving in real-world systems.
Dr. Zouaidia Khouloud
Contact:
Email : khouloud.zouaidia@univ-annaba.dz
Disponibily: Monday, Wednesday 13h00 -14h00
Communication"Educational Forum":
All questions related to the course must be asked on the dedicated forum, so that all students can benefit from the answers provided. I commit to responding within a maximum of 48 hours..
Communication by Email:
Email should be used only in case of emergency, particularly if you experience difficulties accessing the platform. In such cases, a response will be provided within 48 hours, except under exceptional circumstances. However, it is important to note that the forum remains the primary communication channel, in order to ensure transparency and accessibility for everyone.
General Objective:
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Bio-inspired approaches have spread across nearly all fields of science, engineering, and industry—from data mining to optimization, from computational intelligence to industrial applications. In fact, bio-inspired computation is one of the most active and popular research areas, with broad multidisciplinary connections.
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The aim of this course is to enable students to become familiar with the main approaches used in bio-inspired computing.
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Prerequisites:
- A brief description of the knowledge required to follow this course.
- Students should have basic concepts of artificial intelligence.
CHAPTER 1: COMPUTER SCIENCE AND NATURE
- Inspiration from Nature
- Synthesis of Natural Phenomena through Computing
- The Notion of Metaphor
- Natural Materials for Computing
CHAPTER 2: EVOLUTIONARY APPROACHES
1. Biological Foundations
2. Principles of Genetic
3. Algorithms Applications
Chapter 3: Swarm Intelligence Approaches
Study of algorithms based on the collective intelligence of simple agents.
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Principles and Methods of Swarm Intelligence
Self-organization, stigmergy, distributed cooperation.
Multi-agent systems inspired by collective behavior. -
Ant Colony Optimization
Pheromone-based optimization (ACO).
Optimal path finding. -
Particle Swarm Optimization
Particle Swarm Optimization (PSO).
Velocity dynamics, individual and global attraction. -
Artificial Bee Colonies
Foraging behavior and optimization through balanced exploration/exploitation. -
Other collective intelligence algorithms
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This chapter was delivered through student-led presentations and python algorithms implementations, which were discussed and enriched with my guidance during VisioConf sessions.
