Transcript CS382 Introduction to Artificial Intelligence

Computer Science & Engineering, University of Nevada, Reno
CS382
Introduction to Artificial Intelligence
Lecture 1:
The Foundations of AI
and Intelligent Agents
24 January 2012
Instructor: Kostas Bekris
382
What is AI?
Humanly
vs.
Rationally
Thinking
“The automation of activities that
“The study of mental faculties
we associate with human thinking,
through the use of computational
activities such as decision-making,
models.”
problem solving, learning”
(Winston, 1992)
(Bellman, 1978)
vs.
“AI is concerned with rational
“The art of creating machines that
action... and studies the design of
perform functions that require
rational agents. A rational agent
intelligence when performed by
acts so as to achieve the best
people”
expected outcome”
(Kurzweil, 1990)
(S.R. & P.N., 1995)
Acting
382
What is AI?
Humanly
vs.
Rationally
Thinking
“The automation of activities that
“The study of mental faculties
we associate with human thinking,
through the use of computational
activities such as decision-making,
models.”
problem solving, learning”
(Winston, 1992)
(Bellman, 1978)
vs.
“AI is concerned with rational
“The art of creating machines that
action... and studies the design of
perform functions that require
rational agents. A rational agent
intelligence when performed by
acts so as to achieve the best
people”
expected outcome”
(Kurzweil, 1990)
(S.R. & P.N., 1995)
Acting
382
Acting Humanly
382
What is AI?
Humanly
vs.
Rationally
Thinking
“The automation of activities that
“The study of mental faculties
we associate with human thinking,
through the use of computational
activities such as decision-making,
models.”
problem solving, learning”
(Winston, 1992)
(Bellman, 1978)
vs.
“AI is concerned with rational
“The art of creating machines that
action... and studies the design of
perform functions that require
rational agents. A rational agent
intelligence when performed by
acts so as to achieve the best
people”
expected outcome”
(Kurzweil, 1990)
(S.R. & P.N., 1995)
Acting
382
Thinking Humanly
382
What is AI?
Humanly
vs.
Rationally
Thinking
“The automation of activities that
“The study of mental faculties
we associate with human thinking,
through the use of computational
activities such as decision-making,
models.”
problem solving, learning”
(Winston, 1992)
(Bellman, 1978)
vs.
“AI is concerned with rational
“The art of creating machines that
action... and studies the design of
perform functions that require
rational agents. A rational agent
intelligence when performed by
acts so as to achieve the best
people”
expected outcome”
(Kurzweil, 1990)
(S.R. & P.N., 1995)
Acting
382
Thinking Rationally
382
What is AI?
Humanly
vs.
Rationally
Thinking
“The automation of activities that
“The study of mental faculties
we associate with human thinking,
through the use of computational
activities such as decision-making,
models.”
problem solving, learning”
(Winston, 1992)
(Bellman, 1978)
vs.
“AI is concerned with rational
“The art of creating machines that
action... and studies the design of
perform functions that require
rational agents. A rational agent
intelligence when performed by
acts so as to achieve the best
people”
expected outcome”
(Kurzweil, 1990)
(S.R. & P.N., 1995)
Acting
382
Acting Rationally
382
382
Where are we now?
382
Intelligent Agents
382
Environments and their properties
382
Environments and their properties
382
How do agents work?
382
Reflex Agents
382
Model-based Reflex Agents
382
Goal-based Agents
382
Utility-based Agents
382
Learning Agents
382
Structure of the Course
Part 1.
Decision-Making in Deterministic Environments
• Single-agent: Dynamic programming and search, informed search and
heuristics, randomized search, constraint satisfaction
• Multi-agent: Adversarial search (mini-max and expecti-mini-max)
Part 2.
Decision-Making in Stochastic Environments
• Single-agent: Bayesian networks, Hidden Markov Models, Kalman and
Particle filters, Decision and Utility theory, (Partially Observable) Markov
Decision Processes
• Multi-agent: Introduction to Game Theory
Part 3.
Introduction to Robotics, Vision and Bio-Inspired AI
• Search in continuous spaces, behaviors, image processing and
understanding, genetic algorithms and neural networks
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What are my personal interests?
Physicall
yGrounde
d
Agents
Robotics
Computer
Games
Human
Assistants
Agents that must and do appropriately model and reason about the
physical properties of their environment:
• algorithmic generation of motion (motion planning)
• state estimation problems given noisy sensors
• and distributed message-passing coordination