Reading assignment

1
Reading assignment

• Chapters 1, 2
• Sections 3.1 and 3.2

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What is artificial intelligence

• Act rationally
• Integrate sub-areas in AI into intelligent agents
• A full breath of potential applications
• Play games
• Control space-rovers
• Cure cancer
• Trade stocks
• Fight wars

3
AI-complete dream

• Robot that saves the world
• Robot that cleans your room
• But
• Its definitely useful, but
• Really narrow
• Hardware is a real issue
• Will take a while
• Whats an AI-complete problem that will be
  useful to a huge number of people in the next
  5-10 years?
• Whats a problem accessible to a large part of AI
  community?

4
What makes a good AI-complete problem?

• A complete AI-system
• Sensing gathering information from the world
• Reasoning making high-level conclusions from
  information
• Acting making decisions that affect the dynamics
  of the world and/or the interaction with the user
• But also
• Hugely complex
• Can get access to real data
• Can scale up and layer up
• Can make progress
• Very cool and exciting

Data gathering can lead to good, accessible and
cool AI-complete problems
5
Factcheck.org

• Take a statement
• Collect information from multiple sources
• Evaluate quality of sources
• Connect them
• Make a conclusion AND provide an analysis

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Automated fact checking
7
Agent

• A concept to help us formalize the
  problem-solving process
• An agent is anything that can be viewed as
  perceiving its environment through sensors and
  acting upon that environment through actuators
• Human agent eyes, ears, and other organs for
  sensors hands, legs, mouth, and other body parts
  for actuators

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An AI agent

• http//www.youtube.com/watch?vhyGYasf5rKc

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Vacuum-cleaner world

• Percepts location and contents, e.g., A, Dirty
• Actions move-left, move-right, suck

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Rational agents

• An agent should strive to "do the right thing",
  based on what it can perceive and the actions it
  can perform. The right action is the one that
  will cause the agent to be most successful
• Performance measure An objective criterion for
  success of an agent's behavior

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Vacuum-cleaner world

• Percepts location and contents, e.g., A, Dirty
• Actions move-left, move-right, suck
• Performance measure award one point for each
  clean square at each time step, over a lifetime
  of 1000 time steps
• What should be rational actions?

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Rational agents

• Rational Agent For each possible percept
  sequence, a rational agent should select an
  action that is expected to maximize its
  performance measure, given the evidence provided
  by the percept sequence and whatever built-in
  knowledge the agent has.

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A simple agent function

• A rational agent given the performance measure,
  and the geography is known (why?)
• What if a different performance measure is used?
• e.g. deduct one point each time the vacuum moves
• What if the geography is not known?

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An other example

• The savage game
• Performance measure minimize the total number of
  steps
• Environment known
• How to design a rational agent?

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PEAS specifying the setting for the agent

• PEAS Performance measure, Environment,
  Actuators, Sensors
• Performance measure
• Environment
• Actuators
• Sensors

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PEAS

• Must first specify the setting for intelligent
  agent design
• Consider, e.g., the task of designing an
  automated taxi driver
• Performance measure Safe, fast, legal,
  comfortable trip, maximize profits
• Environment Roads, other traffic, pedestrians,
  customers
• Actuators Steering wheel, accelerator, brake,
  signal, horn
• Sensors Cameras, sonar, speedometer, GPS,
  odometer, engine sensors, keyboard

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Environment types

• Fully observable (vs. partially observable) An
  agent's sensors give it access to the complete
  state of the environment at each point in time.
• Deterministic (vs. stochastic) The next state of
  the environment is completely determined by the
  current state and the action executed by the
  agent.

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Partially observable
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Stochastic environment
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Environment types

• Static (vs. dynamic) The environment is
  unchanged while an agent is deliberating
• Discrete (vs. continuous) A limited number of
  distinct, clearly defined percepts and actions
• Single agent (vs. multiagent) An agent operating
  by itself in an environment

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State Space Formulation

• Let us start from the simplest form
• Fully observed, deterministic, static, discrete,
  single agent
• A natural way to represent the problem is called
  State Space Formulation
• Consider the river-crossing example
• Key idea represent the facts by states, and
  actions by state transitions

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Example Romania
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Example Romania

• On holiday in Romania currently in Arad.
• Flight leaves tomorrow from Bucharest
• Formulate goal
• be in Bucharest
• Formulate problem
• states various cities
• actions drive between cities
• Find solution
• sequence of cities, e.g., Arad, Sibiu, Fagaras,
  Bucharest

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State-space problem formulation

• A problem is defined by four items
• initial state e.g., "at Arad"
• actions or successor function S(x) set of
  actionstate pairs
• e.g., S(Arad) ,
• goal test, can be
• explicit, e.g., x "at Bucharest"
• implicit, e.g., Checkmate(x)
• path cost (additive)
• e.g., sum of distances, number of actions
  executed, etc.
• c(x,a,y) is the step cost, assumed to be 0
• A solution is a sequence of actions leading from
  the initial state to a goal state
• Whats the problem formulation for two travelers?

25
Abstraction

• Real world is absurdly complex
• ? state space must be abstracted for problem
  solving
• (Abstract) state set of real states
• (Abstract) action complex combination of real
  actions
• e.g., "Arad ? Zerind" represents a complex set of
  possible routes, detours, rest stops, etc.
• (Abstract) solution
• set of real paths that are solutions in the real
  world

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Example vacuum world

• What is the state space transition graph?
• Single-state, start in 5. Solution?

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Vacuum world state space graph

• states?
• actions?
• goal test?
• path cost?

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Vacuum world state space graph

• states? Dirty? and robot location
• actions? Left, Right, Suck
• goal test? no dirt at all locations
• path cost? 1 per action

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Example The 8-puzzle

• states?
• actions?
• goal test?
• path cost?

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Example The 8-puzzle

• states? locations of tiles
• actions? move blank left, right, up, down
• goal test? goal state (given)
• path cost? 1 per move

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Multiplication of state-space

• Often the problem involves multiple entities a
  combination of multiple subproblems
• Cartesian products of search space