CORE

Swarm Intelligence

24CSE861 · S8 · 4 credits

Official KTU 2024 syllabus subject — study with practice, PYQs and AI tools.

Syllabus

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⚡ DAY-BEFORE EXAM

Have an exam tomorrow?

Get a high-yield attack plan focused on maximum marks per minute. Zero fluff, strict PYQ priority, active recall, and trap avoidance.

1. How much time do you have remaining?

Strategy: High-yield concepts + PYQs + weak areas

2. Topic Prioritization (Highest Marks First)Tap a module to mark as weak

PRIORITY A

Module 1

Why:Foundation module

+ Mark Weak

PRIORITY A

Module 2

Why:High exam relevance

+ Mark Weak

PRIORITY B

Module 3

Why:Core module

+ Mark Weak

PRIORITY B

Module 4

Why:Applied concepts

+ Mark Weak

PRIORITY C

Module 5

Why:Standard exam coverage

+ Mark Weak

Modules

Module 01Agent-based modeling (7 hours)expand

Agent-based modeling: Bottom-up modeling method. individual agents. System theory and complex systems. Multi-agent systems, Practical design of intelligent agent System.

Module 02Behavioral swarm intelligence (6 hours)expand

Biological Foundations of Swarm Intelligence, Swarm Intelligence in Optimization, Behavioral swarm intelligence - Modeling flocking behavior. Boids model. Flocking behavior applications - agents queuing and homing.

Module 03Computational Swarm Intelligence-I (7 hours)expand

Optimization theory and multi-objective optimization. Particle swarm optimization (PSO) – Algorithm, PSO System Parameters, Modifications to PSO, Applications, PSO Algorithm Based on Graphic Processing Units.

Module 04Computational Swarm Intelligence-II (9 hours)expand

Ant colony optimization (ACO) – Algorithm, Ant Colonies and Clustering, Applications. Bees colony optimization (BCO)- Algorithm, Artificial Bees Colony (ABC), Parallel Approaches for the Artificial Bee Colony Algorithm, Bumble Bees Mating Optimization Algorithm for the Vehicle Routing Problem.

Module 05Advanced Swarm Techniques) (7 hoursexpand

Optimization Based-On Hybrid Swarm Intelligence, Glowworm Swarm Optimization for Multimodal Search Spaces, Direct and Inverse Modeling of Plants Using Cat Swarm Optimization, Parallel Bacterial Foraging Optimization. Swarm robotics.

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