Physical Symbol System Hypothesis, AI Technique

1. Problem Solving through Artificial
Intelligence
Lecture-05
Hema Kashyap

2. Physical Symbol System Hypothesis
• Assumption-Cognition is the form of information processing(how human
thinks / how human brain works)
• Two modes of information process:-
– Physical Symbol system hypothesis- Eg. Turing machine model of
information processing associated with classical ,symbolic AI
– Connectionism/ Artificial Neural Network- neurally inspired model
of information processing. It is used to model cognitive/perceptual
abilities that have posed problems for classical AI
• A physical symbol system has the necessary and sufficient means for
intelligent action
– Necessity: Anything capable of intelligent action is a physical symbol
system
– Sufficiency: Any PSS is capable of intelligent action

3. 4 basic ideas
• Symbols are physical patterns
• Symbols can be combined to form complex symbol structure
• The symbol contains processes for manipulating complex
symbol structure
• The process of representing complex symbol structures can
themselves by symbolically represented within the symbol.

4. AI Technique
Intelligence requires knowledge but knowledge possesses less desirable properties such
as
- It is voluminous
- it is difficult to characterise accurately
- it is constantly changing
- it differs from data by being organised in a way that corresponds to its application
An AI technique is a method that exploits knowledge that is represented so that
- The knowledge captures generalisations; situations that share properties, are grouped
together, rather than being allowed separate representation.
- It can be understood by people who must provide it; although for many programs the
bulk of the data may come automatically, such as from readings. In many AI domains
people must supply the knowledge to programs in a form the people understand and in
a form that is acceptable to the program.
- It can be easily modified to correct errors and reflect changes in real conditions.
- It can be widely used even if it is incomplete or inaccurate.
- It can be used to help overcome its own sheer bulk by helping to narrow the range of
possibilities that must be usually considered.

5. Problem Spaces and Search
• To build a system to solve a particular problem, we need to do
four things:
– Define the problem precisely (Initial state, final state, or
acceptable solutions)
– Analyze the problem(features that have dominant affect on
chosen solution)
– Isolate and represent the task knowledge (necessary to
solve problem)
– Choose the best problem-solving technique(s) and apply
it(them).

6. Defining a problem as State Space
• Define a state space (all possible states including initial and
goal states)
• Specify the initial state
• Specify one/ more acceptable goal states
• Specify the set of rules that describes the actions(operators)
available

7. Formal description of a problem
• Define a state space that contains all possible configurations of the relevant objects,
without enumerating all the states in it. A state space represents a problem in terms of
states and operators that change states
– Define some of these states as possible initial states;
– Specify one or more as acceptable solutions, these are goal states;
– Specify a set of rules as the possible actions allowed. This involves thinking about the generality of the
rules, the assumptions made in the informal presentation and how much work can be anticipated by
inclusion in the rules.
• The control strategy is again not fully discussed but the AI program needs a structure
to facilitate the search which is a characteristic of this type of program.

8. Example
The water jug problem :There are two jugs called four and three ; four holds a
maximum of four gallons and three a maximum of three gallons. How can we get 2
gallons in the jug four. The state space is a set of ordered pairs giving the number of
gallons in the pair of jugs at any time ie (four, three) where four = 0, 1, 2, 3, 4 and
three = 0, 1, 2, 3. The start state is (0,0) and the goal state is (2,n) where n is a don't
care but is limited to three holding from 0 to 3 gallons. The major production
rules for solving this problem are shown below:

10. Control Strategy
• A good control strategy should have the following requirement: The first
requirement is that it causes motion. In a game playing program the pieces move on
the board and in the water jug problem water is used to fill jugs. The second
requirement is that it is systematic, this is a clear requirement for it would not be
sensible to fill a jug and empty it repeatedly nor in a game would it be advisable to
move a piece round and round the board in a cyclic way. We shall initially consider
two systematic approaches to searching.