“How can I learn AI?” - HEA ICS

blabbedharborIA et Robotique

23 févr. 2014 (il y a 3 années et 1 mois)

46 vue(s)

“How can I learn AI?”

Lindsay Evett, Alan Battersby,
David Brown, SCI NTU

Penny Standen, DRA UN

Application
-
Based Teaching


Relevance


Active enquiry and exploration


Can be case based


Constructivist


Kolb Accommodating (Concrete
Experience/Active Experimentation)


Supports more traditional methods
(lectures, seminars)


blended learning


Real Applications


Real applications which are publicly and
easily available


Some demonstrable success


More convincing than text book
toy/engineered examples


While evaluation data often lacking they
are braving the open market


Current Practical Work


Chatbots


Topic bridges AI and NLP; so highly
suitable for my AI&NLP module


Applications


interfaces in general, IKEA
call centre, search engines, Virtual
help/assistant, naughty chat lines……


Mostly work through pattern matching


Chatbot methods?


Available chatbots methods elusive


Jabberwacky says no single recognised AI
technique


complex layered heuristics


Others perhaps some form of knowledge
bases to produce learning, personalities,
knowledge, unclear how


Coursework Requirements


The coursework requires students to use
simple forms of AI&NLP techniques to
improve conversation of a simple, ELIZA
type, pattern matching Chatbot


The Chatbot provided has optional


Speech output


Lexicon


Lots of scope


Learning Outcomes


Use, apply and critically evaluate major
techniques used in AI and NLP


Analyse, design and develop AI
computer applications



Solve problems using AI and NLP
techniques


Use and apply basic algorithmic and
design approaches

Future Developments


Intelligent virtual tutors


Could be knowledge based


Could be proactive (need to identify
situations and act appropriately)


Could have conversations, discussions,
answer questions (Chatbots incorporated)


Plenty of scope

Intelligent Virtual Tutor Agents


Unobtrusive but reactive/proactive tutoring
agents


Monitor student actions and visit when
need arises, giving advice and/or
instructions


Can need knowledge for monitoring


Types of Tutors

Deductive tutor agents
: give advice on deductive
reasoning, (e.g., NDSU Geology Explorer
http://oit.ndsu.edu/menu/
):



a. Equipment Tutor



b. Exploration Tutor




c. Science Tutor

Case
-
based tutor agents
: present relevant
cases/experience (e.g., video to demonstrate
experimental procedures (Yu et al 2005))

Types of Tutors (contd.)

Rule
-
based tutor agents
:

a. encode set of rules about domain.

b. Monitor student actions for broken rules

c. Visit student to provide expert dialogue or
tutorial

Navigational tutor agents:
supply context
dependant information to aid navigational
tasks (e.g., Quest
http://quest.isrg.org.uk
)


Develop Tutors


Virtual Health Clinic
www.isrg.org.uk/VHC


Currently presents information as text
when necessary (information buttons)


Clinic as environment, many opportunities
for simple interventions


Receptionist ++…….?



Other Suitable AI Applications?


Game AI


many different methods involved


Speech XML


Tagging, Data Mining


Knowledge tools


search engines, Semantic
Web, Ontology tools


Pattern recognition


Robots


toys, prosthetics



NB evaluation of many applications is lacking


Conclusions


Quite a few Weak AI successes


Mostly procedural


Not really intelligent?


A few have a range of methods


Becoming part of the pervasive
background


Soft computing type systems as the basis
for developing higher order cognition?