📘 NIC

NATURE INSPIRED COMPUTING

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NIC Unit 1: EVOLUTIONARY COMPUTING

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NIC Unit 2: NEUROCOMPUTING

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NIC Unit 3: SWARM INTELLIGENCE

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NIC Unit 4: IMMUNOCOMPUTING

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NIC Unit 5: Case Studies

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Syllabus Overview

UNIT - I Evolutionary Computing

Foundations of Evolutionary Computing

  • Problem Solving as a Search Task
  • Hill Climbing Algorithm
  • Simulated Annealing
  • Introduction to Evolutionary Biology
  • Evolutionary Computing Concepts
  • Other Main Evolutionary Algorithms (Genetic Algorithms, Genetic Programming, Evolution Strategies, Differential Evolution)
  • From Evolutionary Biology to Computing
  • Scope and Applications of Evolutionary Computing

UNIT - II Neurocomputing

Artificial Neural Networks and Neurocomputing

  • The Human Nervous System (Biological Inspiration)
  • Artificial Neural Networks (ANNs): Structure and Function
  • Typical ANN Architectures (Perceptron, MLP, RBF, etc.)
  • Learning Algorithms (Supervised, Unsupervised, Reinforcement)
  • Backpropagation, Hebbian Learning, Competitive Learning
  • From Natural to Artificial Neural Networks
  • Scope and Applications of Neurocomputing

UNIT - III Swarm Intelligence

Swarm Intelligence Systems

  • Ant Colony Optimization (ACO)
  • Foraging Behavior and Pheromone Models
  • Swarm Robotics: Coordination and Collective Behavior
  • Social Adaptation of Knowledge in Swarms
  • Particle Swarm Optimization (PSO)
  • Applications in Optimization, Robotics, and Scheduling

UNIT - IV Immunocomputing

Artificial Immune Systems

  • The Human Immune System (Biological Foundation)
  • Artificial Immune Systems (AIS): Principles and Models
  • Bone Marrow Models
  • Negative Selection Algorithms
  • Clonal Selection and Affinity Maturation
  • Artificial Immune Networks
  • From Natural Immune System to Artificial Immune Systems
  • Scope and Applications of AIS (Anomaly Detection, Optimization, Pattern Recognition)

UNIT - V Case Studies and Applications

Real-World Applications of Nature-Inspired Computing

  • Case Study: Bioinformatics (Gene Prediction, Protein Folding, Sequence Alignment)
  • Case Study: Information Display and Visualization (Swarm-based UI, Immune-inspired Data Clustering)
  • Hybrid Nature-Inspired Models
  • Emerging Trends and Future Directions
NATURE INSPIRED COMPUTING Notes