What is artificial intelligence?

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The physical symbol system

•set of entities==> symbols

•All symbols/instances related in some physical way.

•Processes(creation, modification, reproduction and destruction)

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Intelligence requires knowledgeKnowledge-

1. Voluminous

2. Hard to categorize

3. Constantly changing

4. Organisation different to usage

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What is an AI technique?

•Should capture generalisation

•Understood by people who provide it

•Easily modified to correct errors and reflect changes

•Mostly accurate

•Overcome bulk possibilities to produce result

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3 important AI techniques?Search

Use of knowledge

Abstraction

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4 steps to solve a problem•Define problem precisely

•Analyse problem

•Isolate and represent task knowledge necessary

•Choose best problem solving technique

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State space representation

• Basis of AI methods

• Structure:-

• Formal definition for problem

• Explore space trying to find path from current state to goal state

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State space problem

•Define state space (all possible configurations of relevant objects)

•Specify initial state

•Specify goal state

•Specify set of rules that define actions

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Production System•Rules : Applicability ->Operation

•Knowledge/Databases

•Control strategy

•Rule applier

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Control Strategy requirements•It should cause motion

•It should be systematicshreya chakraborty

Breadth-first

Searchshreya chakraborty

Depth-first

Searchshreya chakraborty

Heuristic SearchHeuristic Knowledge incorporated in search

• in rules themselves

• or as a function

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Heuristic function• Problem description

measures(numbers)

• F(x)=g(x)+h’(x)

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Problem characteristics•Decomposable?•Solution steps can be undone?•Problem’s universe predictable?•Good solution obvious?•Desired solution a state or a path?•Large amt of knowledge absolutely required to solve the problem/•Can computer take problem and return solution?

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Issues in Search Program Design

*instead of building entire tree, programs represent trees in rules implicitly, and generate what needs to be explored

*forward vs backward reasoning

*rule matching

*knowledge representation problem and frame problem

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Heuristic Search techniques1. Depth First

2. Breadth Firstshreya chakraborty

3. Generate and Test

• Generate solution

• Check to see if actually a solution by comparison

• If solution found quit, else repeat all steps

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4. Hill Climbing

• Simple Hill Climbing

• Steepest Ascent Hill Climbing

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5. Best First Search

• Or-graphs

• A* algorithm

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using REDUCE-AND

· Use REDUCE on each immediate subgoal until there are

no more subgoals, or until REDUCE finds a subgoal that

is not satisfied.

· If REDUCE has found a subgoal that is not satisfied,

announce that the goal is not satisfied; otherwise,

announce that the goal is satisfied.

using REDUCE-OR

· Use REDUCE on each subgoal until REDUCE finds a

subgoal that is satisfied.

· If REDUCE has found a subgoal that is satisfied,

announce that the goal is satisfied; otherwise, announce

that the goal is not satisfied.

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6. Problem Reduction

• And-or graphs

• AO* algorithm

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8. Constraint Satisfaction

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8. Constraint Satisfaction

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9.Mean Ends Analysis

To perform means-ends analysis,· Until the goal is reached or no more procedures areavailable,- Describe the current state, the goal state, and

the difference between the two.- Use the difference between the current state

and goal state, possibly with the description ofthe current state or goal state, to select apromising procedure.

- Use the promising procedure and update thecurrent state.

· If the goal is reached, announce success; otherwise,announce failure.

shreya chakraborty