AI-Assignment 2
SUBMITTED TO: SIR AWAIS
IRFAN BASHIR 12347
Question # 1: Describe a rational agent function for the case in which each
movement costs one point. Does the corresponding agent program require
internal state?
For the case in which each movement costs one point, the agent should stop after checking
both A and B squares and eliminating any dirt found in order to reduce unnecessary
movements and loss of points. The corresponding agent program would require internal state
in this case, as it would essential to remember checking both squares before it stops execution
its task. If it finds dirt at square A, cleans it, then moves to square B and finds no dirt, and then
does not remember whether or not it checked square A, it will check A again, and then repeat
with square B and continue making unnecessary movements, thus losing points.
If the squares did not permanently remain clean, however, the agent could stop for some fixed
amount of time after checking and cleaning both squares and repeat its task. It could work at
some time interval, checking both squares, cleaning any dirt found, stopping for 1 hour or so,
and then repeating the process. This would allow the agent to minimize movements and point
loss while keeping the squares clean if they were to become dirty again.
Question #2: For each of the following activities, give a PEAS description of the
task environment and characterize it in terms of the properties of task
environment.
 Playing soccer.
P- Win/Lose Upper body S- Eyes, Ears. Partially observable, E- Soccer field A- Legs, Head,
multiagent, stochastic, sequential, dynamic, continuous, un-known.
 Exploring the subsurface oceans of Titan.
A- steering, accelerator, break, probe arm, S- camera, sonar, probe sensors. partially
observable, single agent, P- Surface area mapped, extraterrestrial life found E- subsurface
oceans of Titan stochastic, sequential, dynamic, continuous, unknown
 Shopping for used AI books on the Internet
P- Cost of book, partially observable, multiagent, stochastic quality/relevance/correct edition
E- Internet’s used book shops A- key entry, cursor S- website interfaces, browser. Sequential,
dynamic, continuous, unknown
 Playing a tennis match.
P- Win/Lose, Legs, S- Eyes, Ears. partially observable, multiagent, E- Tennis court A- Tennis
racquet, stochastic, sequential, dynamic, continuous, unknown
 Practicing tennis against a wall.
P- Improved performance in future tennis matches, E- Near a wall A- Tennis racquet, Legs SEyes, Ears. observable, single agent, stochastic, sequential, dynamic, continuous, unknown
 Performing a high jump.
P- Clearing the jump or not E- Track A- Legs, Body,S- Eyes. observable, single agent, stochastic,
sequential, dynamic, continuous, unknown
 Knitting a sweater.
P- Quality of resulting sweater E- Rocking chair A- Hands,Needles,S- Eyes. observable, single
agent, stochastic, sequential, dynamic, continuous, unknown
 Bidding on an item at an auction.
P- Item acquired, Final price paid for item, E- Auction House (or online) A- Bidding S- Eyes,
Ears. Partially observable, multiagent, stochastic (tie-breaking for two simultaneous bids),
episodic, dynamic, continuous, known
Question # 3: Provide two situations / scenarios each which fulfills the
requirements of the nature of following Environments. Also provide arguments
that categorizes the given scenario / situations into the following environment.
The example scenarios and situations should not be coming from the book
examples
1. Fully Observable environment
An environment is called Fully Observable is when the information received by your agent at
any point of time is sufficient to make the optimal decision.
Scenario 1: In a Tic-Tac-Toe game, seeing the position of the elements on the board is enough
to make an optimal decision on the next move.
Scenario 2: In a chess game, the state of the system, that is, the position of all the players on
the chess board, is available the whole time so the player can make an optimal decision.
2. Partially Observable environment
An environment is called Partially Observable is when the agent needs a memory in order to
make the best possible decision.
Scenario 1: In a Poker game, the agent needs to remember the previous moves in order to
make a best possible decision. Which is why it needs a memory.
Scenario 2: Driving – the environment is partially observable because what’s around the corner
is not known
3. Deterministic Environment
An environment is called Deterministic is where your agent’s actions uniquely determine the
outcome.
Scenario 1: In Chess, there is no randomness when you move a piece.
Scenario 2: if we had a pawn while playing chess and we moved that piece from A2 to A3, that
would always work. There is no uncertainty in the outcome of that move.
4. Stochastic Environment
An environment is called Stochastic is where your agent’s actions don’t uniquely determine the
outcome.
Scenario 1: In games with dice, you can determine your dice throwing action but not the
outcome of the dice.
Scenario 2: Self Driving Cars – the actions of a self-driving car are not unique, it varies time to
time
5. Episodic Environment
In an episodic environment, there is a series of one-shot actions, and only the current percept is
required for the action.
Scenario 1: An AI that looks at radiology images to determine if there is a sickness is an example
of an episodic environment
Scenario 2: An AI that looks at radiology images to determine if there is a sickness is an example
of an episodic environment.
6. Sequential Environment
Scene 1: With a chess agent, each new action depends upon what happened previously. Or, in
other words, different actions can have different consequences. Using your queen to take your
opponent’s knight may bring short-term utility, but it may also put your queen at risk in the
next move. This is a sequential environment.
Scene 2: Brushing your teeth
7. Dynamic Environment
A dynamic environment is changing rapidly. Managers must react quickly and organizations
must be flexible to respond.
Scenario 1: Today's business environment is generally very dynamic. Technology, consumer
tastes, laws and regulations, political leaders, and international conditions are all changing
rapidly and dramatically.
Scenario 2: Roller coaster ride is dynamic as it is set in motion and the environment keeps
changing every instant.
8. Static Environment
An environment is static if only the actions of an agent modify it. ... An environment is said to
be discrete if there are a finite number of actions that can be performed within it.
Scenario 1: An empty house is static as there’s no change in the surroundings when an agent
enters.
Scenario 2: Empty office with no moving objects