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        <description>Lab 1 - Agents

Problem Description

Implement the control program for a vacuum cleaner agent.
The environment is a rectangular grid of cells which may contain dirt or an obstacle. The agent is located in this grid and facing in one of the four directions: north, south, east or west.
The agent can execute the following actions:</description>
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        <description>Lab 2 - Formulating Search Problems

Problem Description

Consider an agent for playing Backgammon.
You can see an example match here.

Tasks

Formulate the search problem, that is,

	*  find a representation (data structure) for states
	*  find a representation (data structure) for actions</description>
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        <description>Part 1 - Propositional Logic / Resolution

(Based on “The Adventure of Silver Blaze,” an original Sherlock Holmes mystery by Arthur Conan Doyle)

A prize-winning racehorse named Silver Blaze has been stolen from a stable, and a bookmaker named Fitzroy Simpson has been arrested as the prime suspect by good old Inspector Gregory. Sherlock Holmes, however, after ample use of his magnifying glass and some of the strongest black tobacco this side of the Atlantic, finds the true thief by reasoning fro…</description>
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        <description>Lab 4: Bayesian Networks

In this session we will look at some basic Bayesian Networks and you will solve two problems using a Bayesian Network simulator.
You can work together in groups. Hand in the results in MySchool, this lab counts as one assignment.</description>
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        <description>Learning Decision Trees

Material:

	*  [java project]

Tasks:

	*  Change the existing code, so that it prints (the necessary data) for a learning curve.
	*  Plot the learning curves for all three data sets (monk-1, monk-2, monk-3) and interpret them.
	*  Are the trees that are learned consistent with the training data? If not, what could be the reason?</description>
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        <description>Lab 6: Particle Filter

In this session we will look at how to use particle filtering for localization of a robot.
You can work together in groups. Hand in the results in MySchool, this lab counts as one assignment.

Material

Download the following file:</description>
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        <description>T-622-ARTI, Introduction to Artificial Intelligence, Spring 2012

Basic Info

	*  Instructor:  Stephan Schiffel (stephans+ru.is)
	*  Office:  3rd floor, Venus, 695-2998
	*  Theory Lectures:  Tuesdays 13:10-14:45 (M123), Thursdays 9:20-10:05 (M109) 
	*  Labs:  Thursdays 13:10-14:45 (M106)</description>
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        <description>Programming Assignment 1 - Search

Use the forum or email me, if you have any questions or problems with the assignment. Start early, so you still have time to ask in case of problems!

Problem Description

Find a good plan for the vacuum cleaner agent.
The Environment is still the same as in</description>
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        <description>Programming Assignment 2 - Adversarial Search

Use the forum or email me, if you have any questions or problems with the assignment. Start early, so you still have time to ask in case of problems!

Problem Description

Implement an agent that is able to play</description>
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