Special Note: The class is now over. No class on March 12.
Overview: What is Intelligence?
is that quality that enables an entity to function appropriately and
with foresight in its environment. Intelligent behavior can be arrayed
along a continuum.
Plan of the course: A continuum of ever-more capable "agents"
Prologue to the course: Examples of intelligent agents
Part I: Reactive Agents
Agents that react to simple inputs
Topics: Rule-based actions, several examples
Making agents more intelligent by increasing their perceptual abilities
Topics: visual perception, multi-sensor integration, neural network
learning, deep hierarchical networks, models of the cortex
Making agents more intelligent by giving them "memory"
Topics: maps and map learning, states, how to represent states, state
Learning what action to take depending on state
Topics: Reinforcement learning, model helicopter control, TDgammon, summary
Part II: Agents that Make Plans
What is required for a planning agent
Topics: State representation, how actions change state, how to
recognize a goal state
Representing states and actions in a graph
Topics: Finding paths in maps, the 8-puzzle, breadth-first
search, heuristic search (A*)
Representing states by lists of what's true and how these lists change due to actions
Topics: STRIPS rules, forward and backward search
Games (Adversarial Search)
Topics: Limits on search, evaluation functions, minimax search,
some commercial chess and Go
Part III: Agents that Reason
Topics: syllogisms, logic, deductions vs abductions, proving theorems,
applications of automated theorem proving
Semantic networks and taxonomies
Topics: CYC, Word Net, Image Net Using uncertain information
Topics: Probabilities, Bayesian networks
Part IV: Agents that Understand Human Language
Topics: waveform features -> phonemes -> words, hidden markov models Text understanding
Topics: syntactic, semantic, and pragmatic analyses
Use of Large Corpora
Part V: Evolutionary AI
Topics: Genetic Algorithms, Genetic Programming
Part VI: Putting it all Together -- Robotics Topics: Examples of robots, robot architectures
Part VII: Social Implications of AI Topics: Benificial and Worrisome Effects, Military Robots, Privacy, Employment, . . . .
Links to lecture slides
(Movies and animations do not play in the pdf files, but they should work in the ppsx files.)Jan 8 PDF Format (30 MB) Jan 8 PPSX Format (24 MB)Jan 15 PDF Format (9 MB) Jan 15 PPSX Format (10 MB) Jan 22 PDF Format (10.6 MB) Jan 22 PPSX Format (9.6 MB)Jan 29 PDF Format (5.3 MB) Jan 29 PPSX Format (7.3 MB) Feb 5 PDF Format (3.3 MB) Feb 5 PPSX Format (35 MB) Feb 12 PDF Format (4.7 MB) Feb 12 PPSX Format (3.4 MB)Feb 19 PDF Format (4.1 MB) Feb 19 PPSX Format (45 MB)
-- This link actually takes you to my Stanford siteFeb 26 PDF Format (24 MB) Feb 26 PPSX Format (300 MB !)
Mar 5 PDF Format (1.1 MB) Mar 5 PPSX Format (1.1 MB)