1 / 12

Overview of AI

Overview of AI. 2005/03/03. Outline. Introduction A brief history AI methods Problem solving Knowledge representation and reasoning Learning Research areas Related resources. Introduction. Motivation

malha
Download Presentation

Overview of AI

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Overview of AI 2005/03/03

  2. Outline • Introduction • A brief history • AI methods • Problem solving • Knowledge representation and reasoning • Learning • Research areas • Related resources

  3. Introduction • Motivation • The aims of AI reflect ancient dreams of using minds and hands to create beings like human. • Definition • AI is a branch of science which deals with helping machines find solutions to complex problems in a more human-like fashion.

  4. A brief history • Chess program (Shannon and Turing, 1953) • General problem solver (Newell and Simon, 1956) • Lisp (McCarthy, 1958) • MYCIN (Feigenbaum et al., 1969) • PROSPECTOR (Duda et al., 1979) • Intelligent system (Pearl et al., 1988) • PEAGASUS (Zue et al., 1994)

  5. AI methods- Problem solving • The goal of problem solving is to decide what to do by finding sequences of actions that lead to desirable states. • Search strategies: • Breadth-first search • Depth-first search • Hill-climbing search • Best-first search • A* search • Mini-Max algorithm • Alpha-Beta pruning

  6. Al methods- Knowledge and reasoning • A knowledge-based system uses logical reasoning to maintain a description of the world as new percepts arrive, and to deduce a course of action that will achieve its goals. • Certain environment: • First-order logic • Case-based reasoning

  7. AI methods- Knowledge and reasoning • Uncertain environment: • Probability theory • Fuzzy theory • Stochastic simulation

  8. AI methods- Learning • The idea behind learning is that percepts should be used not only for acting, but also for improving the ability to act in the future. • Learning methods: • Inductive learning • Neural network • Brief network

  9. Research areas • Knowledge representation and articulation • Learning and adaptation • Deliberation, planning, and acting • Speech and language processing • Image understanding and synthesis

  10. Research areas • Manipulation and locomotion • Autonomous agents and robots • Multiagent systems • Cognitive modeling • Mathematical foundations

  11. Related resources • Conferences • International Joint Conference on Artificial Intelligence (IJCAI) • The National Conference on Artificial Intelligence (AAAI) • International Conference on Machine Learning (ICML) • Journals • Artificial Intelligence • Journal of Artificial Intelligence Research • AI Magazine • IEEE intelligent systems

  12. Related resources • Organizations • American association for artificial intelligence (AAAI) • ACM Special Interest Group in Artificial Intelligence (SIGART) • Society for Artificial Intelligence and Simulation of Behaviour (AISB) • Web sites • http://www.cs.berkeley.edu/~russell/ai.html • http://www.ics.uci.edu/~mlearn/MLRepository.html (UCI Machine Learning Repository)

More Related