CS451CS551EE565 ARTIFICIAL INTELLIGENCE

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CS451/CS551/EE565ARTIFICIAL INTELLIGENCE

• Search
• 9-4-2006
• Prof. Janice T. Searleman
• jets_at_clarkson.edu, jetsza

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Outline

• Other Intelligent Agents
• mobile
• information
• Search
• HW2 posted due Wednesday, 9/6/06

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Mobile agents

• Programs that can migrate from one machine to
  another.
• Execute in a platform-independent execution
  environment.
• Require agent execution environment (places).
• Mobility not necessary or sufficient condition
  for agenthood.
• Practical but non-functional advantages
• Reduced communication cost (eg, from PDA)
• Asynchronous computing (when you are not
  connected)
• Two types
• One-hop mobile agents (migrate to one other
  place)
• Multi-hop mobile agents (roam the network from
  place to place)
• Applications
• Distributed information retrieval.
• Telecommunication network routing.

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Mobile agents

• Programs that can migrate from one machine to
  another.
• Execute in a platform-independent execution
  environment.
• Require agent execution environment (places).
• Mobility not necessary or sufficient condition
  for agenthood.

A mail agent
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Mobile agents

• Practical but non-functional advantages
• Reduced communication cost (e.g. from PDA)
• Asynchronous computing (when you are not
  connected)
• Two types
• One-hop mobile agents (migrate to one other
  place)
• Multi-hop mobile agents (roam the network from
  place to place)

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Mobile agents

• Applications
• Distributed information retrieval.
• Telecommunication network routing.

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Information agents

• Manage the explosive
• growth of information.
• Manipulate or collate information
• from many distributed sources.
• Information agents can be mobile or static.
• Examples
• BargainFinder comparison shops among Internet
  stores for CDs
• Internet Softbot infers which internet facilities
  (finger, ftp, gopher) to use and when from
  high-level search requests.
• Challenge ontologies for annotating Web pages
  (eg, OWL).

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How is an Agent different from other software?

• Agents are autonomous, that is, they act on
  behalf of the user
• Agents contain some level of intelligence, from
  fixed rules to learning engines that allow them
  to adapt to changes in the environment
• Agents don't only act reactively, but sometimes
  also proactively

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How is an Agent different from other software?

• Agents have social ability, that is, they
  communicate with the user, the system, and other
  agents as required
• Agents may also cooperate with other agents to
  carry out more complex tasks than they themselves
  can handle
• Agents may migrate from one system to another to
  access remote resources or even to meet other
  agents

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Summary Agents

• Intelligent Agents
• Anything that can be viewed as perceiving its
  environment through sensors and acting upon that
  environment through its effectors to maximize
  progress towards its goals.
• PAGE (Percepts, Actions, Goals, Environment)
• Described as a Perception (sequence) to Action
  Mapping f P ? A
• Using look-up-table, closed form, etc.
• Agent Types reflex, state, goal-based,
  utility-based
• Rational Action The action that maximizes the
  expected value of the performance measure given
  the percept sequence to date

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Solving Problems by Searching
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Outline

• Problem-solving agents
• Problem types
• Problem formulation
• Example problems
• Basic search algorithms

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What is a problem?

• want to achieve a goal, but there is no direct
  way to do it

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Problems???

• In the middle of taking the GREs, your only 2
  pencil breaks
• 15-puzzle
• Instant Insanity build a tower of 4 blocks so
  that each of the 4 colors shows on each of the 4
  sides of the tower
• Typographical Rebus (wacky wordies)
• Monk on the Mountain

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Typographical Rebuses
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Monk on the Mountain

• One day an old monk decides to leave his
  monastery at precisely 600 am to climb to the
  top of a mountain so he can enjoy its solitude.
  He travels at various speeds and takes several
  rests before arriving at the mountain peak at
  precisely 500 pm. He spends the night in prayer
  and meditation, and starts back down the mountain
  using the same trail the next day at precisely
  600 am, again traveling at different speeds and
  stopping often for periods of rest. At precisely
  500 pm he reaches his starting point back at the
  monastery. Is there some point along the
  mountain trail that he passes at precisely the
  same time each day?

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Steps for Problem Solving

• Goal formulation what is desired
• - may have a set of constraints or measures that
  should be optimized
• - can specify a goal by describing a state in
  which it is achieved, or by giving a goal-test
  function
• Problem formulation what actions states to
  consider
• Search algorithm takes a problem as input
  returns a solution in the form of a sequence of
  actions to take
• Execution carry out the actions

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Problem Formulation

• Representation is a key issue in problem solving.
  How a problem is formulated determines what
  means can be brought to bear to solve the problem
  (and possibly whether or not it can be solved).
• For example, consider designing the
  cross-sectional shape of an airplane wing.
  Possibilities include
• model the wing using mathematical techniques
• build a mockup of the wing and test it in a wind
  tunnel
• create a model in virtual reality
• etc.

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Representation Problem Formulation
Model

• A representation is not just a way of encoding
  the knowledge of a problem
• it determines what means are available for
  working on the problem
• it determines how expensive processing is
• it may determine whether or not all relevant
  knowledge can be encoded

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AI Technique vs. Algorithms

• algorithm to solve the problem may be known, but
  is intractible (e.g. chess)
• no algorithm is known (e.g. playing ping pong)
• algorithms assume complete and consistent data

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Problem-solving agents
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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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Example Romania
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Problem types

• Deterministic, fully observable ? single-state
  problem
• Agent knows exactly which state it will be in
  solution is a sequence
• Non-observable ? sensorless problem (conformant
  problem)
• Agent may have no idea where it is solution is a
  sequence
• Nondeterministic and/or partially observable ?
  contingency problem
• percepts provide new information about current
  state
• often interleave search, execution
• Unknown state space ? exploration problem

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Example vacuum world

• Single-state, start in 5. Solution?

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Example vacuum world

• Single-state, start in 5. Solution? Right,
  Suck
• Sensorless, start in 1,2,3,4,5,6,7,8 e.g.,
  Right goes to 2,4,6,8 Solution?

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Example vacuum world

• Sensorless, start in 1,2,3,4,5,6,7,8 e.g.,
  Right goes to 2,4,6,8 Solution?
  Right,Suck,Left,Suck
• Contingency
• Nondeterministic Suck may dirty a clean carpet
• Partially observable location, dirt at current
  location.
• Percept L, Clean, i.e., start in 5 or
  7Solution?

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Example vacuum world

• Sensorless, start in 1,2,3,4,5,6,7,8 e.g.,
  Right goes to 2,4,6,8 Solution?
  Right,Suck,Left,Suck
• Contingency
• Nondeterministic Suck may dirty a clean carpet
• Partially observable location, dirt at current
  location.
• Percept L, Clean, i.e., start in 5 or
  7Solution? Right, if dirt then Suck

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Single-state 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) ltArad ? Zerind, Zerindgt,
• 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