Fondamenti di Intelligenza Artificiale M
A.A. 2011-2012

• "An introduction to genetic algorithms and genetic programming"

  Andrea Roli - Martedì 17 Aprile 2012, Aula 5.7

  Abstract:
  In this seminar, I will introduce the basic principles and concepts of genetic algorithms (GAs) and genetic programming (GP). These techniques are two representative problem solving methods in the area of evolutionary computation, which is inspired by evolutionary theories. GAs and GP are used to automatically solve problems in optimization, design and control. Notable results have been indeed achieved in several engineering fields and in artificial intelligence.
  The first part of the talk will be devoted to an introduction of the fundamental principles of GAs. The main GA high-level algorithmic scheme will be illustrated, along with its main components. I will briefly survey the simplest version of a GA and provide an outlook to more elaborated versions, along with some representative examples. Subsequently, GP will be introduced as a generalization of the former technique and some successful examples of its application will be outlined.
  

  Lucidi
  Alcuni articoli di interesse:
  1. A Genetic Programming Tutorial, by Koza and Poli
  2. Genetic Algorithms, by Holland
  3. Ant Colony Optimization, by Roli
  4. Swarm Smarts, by Bonabeau and Theraulaz




• "Viaggio al centro della tecnologia semantica: dal trattamento dei Big Data all’analisi del sentiment, passando attraverso il Natural Language Processing"

  Marcello Pellacani (EXPERT SYSTEM) - 16 Maggio 2012 ore 9.00, Aula 3.4

  Abstract:

  • Tecnologie per l'analisi del testo destrutturato: I diversi approcci (keyword, statistico, linguistico, semantico) per la gestione delle informazioni e dei dati strategici. Analisi semantica: le varie fasi.
  • Sensigrafo, la rete semantica di Expert System: Capire con precisione il significato delle parole per sfruttare al meglio i Big Data e la conoscenza contenuta nei documenti
  • Data mining, entity extraction: Estrarre i dati principali per supportare i processi di intelligence
  • Categorizzazione, tassonomie: Ordinare enormi quantità di documenti secondo tassonomie personalizzate
  • Sistemi di self-help in Natural Language Processing: Interagire con gli utenti attraverso la ricerca semantica e l'assistenza in NLP
  • Analisi del sentiment e opinion mining: Supportare con efficacia i processi decisionali tramite l'analisi dei social media
  • Use case ed esempi
    

Lucidi