http://csc375artificialintelligence.wordpress.com/2013/09/30/chapter-2-exercises-2/
2.4) For each of the following activities, give a PEAS description of the task environment and characterize it in terms of the properties listed in Section 2.3.2.
A) Playing soccer.
B) Exploring the subsurface oceans of Titan.
C) Shopping for used AI books on the Internet.
D) Playing a tennis match.
E) Practicing tennis against a wall.
F) Performing a high jump.
G) Knitting a sweater.
H) Bidding on an item at an auction.

2.4)

2.5) Define in your own words the following terms: agent, agent function, agent program, rationality, autonomy, reflex agent, model-based agent, goal-based agent, utility-based agent, learning agent.
2.5)
Agent- A system with at least some form of intelligence.
Agent Function- What at agent is supposed to do, its purpose.
Agent Program- An internal absolute implementation of code.
Rationality- What the agent knows about the environment and a self-judgment on how it performed.
Autonomy- The ability to act on its own. Knowing where it is, what it has to do, etc.
Reflex Agent- Responding to percepts in the environment.
Model Based Agent- Has knowledge of the workings of the world.
Goal Based Agent- Has knowledge of the goal and decides what actions to take in order to reach it.
Utility Based Agent- Determines the best way to reach the goal.
Learning Agent- Analyzes information to make improvements.

2.6) A) Yes, there can be more than one agent program implementing an agent function. As stated above, the function is the purpose and the program is the code for its implementation. If a function has multiple options then there must be more than one program. B) There exist agent functions that cannot be implemented by any agent programs. For example, if an agent function was to count to find the square root of a negative number. There is no way to solve that.
C) Yes, each agent program will implement exactly one agent function. For example, a precept has multiple reactions, but each reaction is different according the situation it’s in. D) There are 2^n possible agent programs. E) Speeding up the machine does not change the agent function because the environment is static.

2.7)
Goal-Based Pseudocode

set tickets_unsold to 50 set tickets_sold to 0

sell tickets for show decrease tickets_unsold for each ticket_sold increase tickets_sold for every decrease in tickets_unsold

stop when tickets_unsold equals zero

Utility-Based Pseudocode

set starting_location to (0,0) set ending_location to (50,50) create a fifty by fifty grid (even numbers are rows, odd numbers are columns) set time to 0

randomly generate two numbers between 1 and 25 (the first is rows and the second is columns) this determines how many roads contain traffic which increases time to ending_location

a normal block takes 1 minute to travel a traffic block takes 5 minutes

start at (0,0) and arrive at (50,50) is the shortest amount of time

compute which path is the shortest and has the least amount of traffic