Click to see the opening montage.
1946: ENIAC heralds the dawn of Computing
I propose to consider the question:
“Can machines think?”
--Alan Turing, 1950
1950: Turing asks the question….
1956: A new field is born
We propose that a 2 month, 10
man study of artificial
intelligence be carried out
during the summer of 1956 at
Dartmouth College in Hanover,
New Hampshire.
- Dartmouth AI Project
Proposal; J. McCarthy et al.;
Aug. 31, 1955.
1996: EQP proves that
Robbin’s Algebras are all boolean
[An Argonne lab program] has come up with a major mathematical
proof that would have been called creative if a human had thought of it.
-New York Times, December, 1996
----- EQP 0.9, June 1996 -----
The job began on eyas09.mcs.anl.gov, Wed Oct 2 12:25:37 1996
UNIT CONFLICT from 17666 and 2 at 678232.20 seconds.
---------------- PROOF ----------------
2 (wt=7) [] -(n(x + y) = n(x)).
3 (wt=13) [] n(n(n(x) + y) + n(x + y)) = y.
5 (wt=18) [para(3,3)] n(n(n(x + y) + n(x) + y) + y) = n(x + y).
6 (wt=19) [para(3,3)] n(n(n(n(x) + y) + x + y) + y) = n(n(x) + y).
…….
17666 (wt=33) [para(24,16426),demod([17547])] n(n(n(x) + x) ….
1997: HAL 9000 becomes operational
in fictional Urbana, Illinois
…by now, every intelligent person knew that
H-A-L is derived from Heuristic ALgorithmic
-Dr. Chandra, 2010: Odyssey Two
1997: Deep Blue ends Human
Supremacy in Chess
I could feel human-level intelligence across the room
-Gary Kasparov, World Chess Champion (human)
vs.
In a few years, even a single victory
in a long series of games would be the triumph of human genius.
For two days in May, 1999, an AI Program called Remote Agent
autonomously ran Deep Space 1 (some 60,000,000 miles from earth)
Real-time Execution
Adaptive Control
HardwareS
cripted
Ex
ecutiv
e
Generative
Planner &
Scheduler
Generative
Mode Identification
& Recovery
Scripts
Mission-levelactions &resources
component models
ESL
Monitors
GoalsGoals
1999: Remote Agent takes
Deep Space 1 on a galactic ride
2002: Computers start passing
Advanced Placement Tests
… a project funded by
(Microsoft Co-founder) Paul
Allen attempts to design a
“Digital Aristotle”.
Its first results involve
programs that can pass High
School Advanced Placement
Exam in Chemistry…
2005: Cars Drive Themselves
Stanley and three other cars drive themselves over a 132 mile mountain road
2005: Robots play soccer
(without headbutting!)
2005 Robot Soccer:
Humanoid league
2006: AI Celebrates its Golden Jubilee…
1956: A new field is born
We propose that a 2 month, 10
man study of artificial
intelligence be carried out
during the summer of 1956 at
Dartmouth College in Hanover,
New Hampshire.
- Dartmouth AI Project
Proposal; J. McCarthy et al.;
Aug. 31, 1955.
2007: Robots Drive on Urban Roads
11 cars drove themselves on urban streets (for DARPA Urban Challenge)
2010: Watson defeats Puny Humans in
Jeopardy!
And Ken Jennings pledges obeisance to the new Computer Overlords..
2014: Robots (instead of them foreigners)
Threaten to Take all your jobs
Winding Our Way
Down To Wall-E:
Adventures in
Artificial Intelligence
Agenda
• What is AI
• AI’s Successes and Expectations
• What is involved in doing AI
• Some ongoing projects in my lab
• Your questions?
Clicking on the
Graphic takes you
To the right webpage
What if we are writing intelligent
agents that interact with humans?
The COG project
The Robotic care givers
Mechanical flight
became possible
only when people
decided to stop
emulating birds…
Open only for Humans; Droids and Robots should go for CSE 462 next door ;-)
Do we want a machine that beats humans in chess or a machine that thinks like humans
while beating humans in chess?
DeepBlue supposedly DOESN’T think like humans..
(But what if the machine is trying to “tutor” humans about how to do things?)
(Bi-directional flow between thinking humanly and thinking rationally)
Default Position Useful for teaming with humans
Useful for tutoring systems
(a form of teaming)
Agenda
• What is AI
• AI’s Successes and Expectations
• What is involved in doing AI
• Some ongoing projects in my lab
• Your questions?
What AI can do is as important as
what it can’t yet do..
• Captcha project
Agenda
• What is AI
• AI’s Successes and Expectations
• What is involved in doing AI
• Some ongoing projects in my lab
• Your questions?
What Makes Agent Design Hard?
A: A Unified Brand-name-Free Introduction to Planning Subbarao Kambhampati
Environment
What action next?
A: A Unified Brand-name-Free Introduction to Planning Subbarao Kambhampati
Environment
Goals
(Static vs. Dynamic)
(Observable vs. Partially Observable)
(perfect vs. Imperfect)
(Deterministic vs. Stochastic)
What action next?
(Instantaneous vs. Durative)
(Full vs. Partial satisfaction)
Architectures for Intelligent Agents
Wherein we discuss why do we need representation, reasoning and learning
(Model-based reflex agents)
How do we write agent programs for these?
This one already assumes that the “sensorsfeatures” mapping has been done!
EXPLICIT MODELS OF THE ENVIRONMENT
--Blackbox models
--Factored models
Logical models
Probabilistic models
(aka Model-based Reflex Agents)
It is not always obvious what action to do now given a set of goals
You woke up in the morning. You want to attend a class. What should your action be?
Search (Find a path from the current state to goal state; execute the first op)
Planning (does the same for structured—non-blackbox state models)
State Estimation
Planning
Representation Mechanisms:
Logic (propositional; first order)
Probabilistic logic
Learning
the models
Search
Blind, Informed
Planning
Inference
Logical resolution
Bayesian inference
How the course topics stack up…
Learning
Dimensions:
What can be learned?
--Any of the boxes representing
the agent’s knowledge
--action description, effect probabilities,
causal relations in the world (and the
probabilities of causation), utility models
(sort of through credit assignment), sensor
data interpretation models
What feedback is available?
--Supervised, unsupervised,
“reinforcement” learning
--Credit assignment problem
What prior knowledge is available?
-- “Tabularasa” (agent’s head is a blank
slate) or pre-existing knowledge
Agenda
• What is AI
• AI’s Successes and Expectations
• What is involved in doing AI
• Some ongoing projects in my lab
• Your questions?
Planning for Human-Robot Teaming
Crowd-sourced planning
Event-analytics
Human-Robot Teaming
59
Search and report (rescue)
Goals incoming on the go
World is evolving
Model is changing
Infer instructions from
Natural Language
Determine goal formulation
through clarifications and
questions
Click for youtube version
Click for youtube version
Teach Me How To Work:
Natural Language Model Updates
Undergraduate
Student Summer
Project
Crowd-Sourced Planning
Yochan lab, Arizona State University
manhattan_gettingto
62
AI-MIX: Crowd Sourced Planning
AI-MIX (Automated Improvement of Mixed Initiative eXperiences)
Commanders
Goal & event generation
A sub-system of RADAR
63
AI-MIX: Crowd Sourced Planning
Force Structure (PDDL) • Reduces flexibility
Extract Structure • Plans from textual descriptions rather than actions
Interpretation
Steering (Model-lite)
Constraint Checking • Quantitative constraints
Constructive Critiques • Actively help creation and refinement of a plan:
suggesting new plan fragments, new ways of decomposing the current plan or set of goals
Winner of the "People's Choice Award" for the best demo at ICAPS 2014!
A sub-system of RADAR
Since the dawn of civilization, people congregated
in town squares to discuss events
The emergence of social media has now created a sprawling virtual town square,
whose scope is vast, and whose chatter can be captured!
opening exciting possibilities for analyzing what people are actually saying..
Which part of the event did a
tweet refer to?
What’s the relation between
event and tweets?
ET-LDA [AAAI’12, ICWSM’12, MMW’12]
Specific
Specific
Specific
General
Specific
General
Specific
General
General
Event Tweets
Determine tweet type
C(t)~Bernoulli(λ)
Determine which
segment a tweet (word)
refers to
S(t) ~ Categorical(γ)
Determine word’s
topic in event
Zs~multinomial(θ)
Tweets word’s topic
Zt~multinomial(ψ) or
Zt~multinomial(θ)
ET-LDA [AAAI’12, ICWSM’12, MMW’12]
Frequency of specific tweets
Event-tweets alignment
Evolution of specific tweets
Specific
Specific
Specific
General
Specific
General
Specific
General
General
SocSent [IJCAI’13]
ET-LDA & SocSent for Event sensemaking
DeMA for Event recognition
Alice for Event engagement prediction
Eventics, automated toolbox to conduct
in-depth analysis of 3 core tasks in
event analytics
How people respond to events on Twitter
What factors affect crowd’s engagement in events
Our toolbox enables a richer
perspective about
Summary & Additional
Resources
• Talked about
– What AI is
– AI’s Successes and Expectations
– What is involved in doing AI
– Some ongoing projects in my lab
– Your questions?
Agenda
• What is AI
• AI’s Successes and Expectations
• What is involved in doing AI
• Some ongoing projects in my lab
• Your questions?
Questions Submitted
• What policy, if any, has been created surrounding this new and developing
technology? Is there any work being done to use AI to improve human
cognition and performance?
• What are ways of combating the existential risks that are put forth by the
development of AI?
• Do you believe that there will ever be functioning domestic humanoid robots
for retail for the general population? (Not just Roombas, bur actual human
looking and functioning bots, or would there too much of an ethical debate on
if it is human?)
• Could we give AI the feeling of curiosity, leading them to have desires for
physical things?
• Yes!
– But this is not going to
be just a question of
hardware
– The robots need to
track the
beliefs/desires/intentio
ns of the humans
• ..and thus our work on
Human-Robot teaming..
• Feeling of Curiosity—
– Yes
– Exploration/Exploitatio
n tradeoff in
Reinforcement
Learning
• Desires for physical
things..
– Hmm..
Questions Submitted
• What policy, if any, has been created surrounding this new and developing
technology? Is there any work being done to use AI to improve human
cognition and performance?
• What are ways of combating the existential risks that are put forth by the
development of AI?
• Do you believe that there will ever be functioning domestic humanoid robots
for retail for the general population? (Not just Roombas, bur actual human
looking and functioning bots, or would there too much of an ethical debate on
if it is human?)
• Could we give AI the feeling of curiosity, leading them to have desires for
physical things?
Summary & Additional
Resources
• Talked about
– What AI is
– AI’s Successes and Expectations
– What is involved in doing AI
– Some ongoing projects in my lab
– Your questions?
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