Evolutionary Algorithms | Lec_7.2 | Swarm Intelligence [SI]: the Particle Swarm Optimisation [PSO]
Welcome to our Evolutionary Algorithms course, where we dive deep into the fascinating world of optimization and natural selection in computing!
What You Will Learn:
1.Popular Evolutionary Algorithm Variantsand taxonomy for Nature-Inspired Algorithms
2.Nature-Inspired Abstraction Models[ a Quick Overview | Why Nature? ]
3.Swarm Intelligence[ a Quick Overview | Emergent Behaviour-from Simplicity to Complexity | the
Interactions: Direct versus Indirect(a.k.a. Stigmergy) | Computational Swarm Intelligence| Swarm
Intelligence versus Genetic Algorithms]
4.Particle Swarm Optimization[PSO] [the Original PSOAlgorithm | the Canonical PSOAlgorithm | Global-best
PSO (𝒈𝒃𝒆𝒔𝒕-PSO) | Local-bestPSO (𝒍𝒃𝒆𝒔𝒕-PSO) | Global-best PSO versus Local-best PSO
5.the Velocity Components[ the Inertia Component | the Cognitive Component (Nostalgia/ Memory) | the
Social Component (Envy/ Cooperation) | the Stopping Criteria]
Resources:
Dr. Amr Ghoneim's drive:
drive.google.com/drive/folder...
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About the Instructor:
I'm Yassen Ahmed, student in Faculty of Computers and Artificial Intelligence, Helwan University (FCAI-HU). I am recording this course to help my colleagues and anyone interested in the same field, and I'm here to share my knowledge and insights with you.
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