Center for Analysis and Design of Intelligent Agents public:t-622-arti-09-1

public:t-622-arti-09-1:final_project

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Final Project The group list has been moved to the proposal page

public:t-622-arti-09-1:final_project_proposal

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Final Project Proposal Groups Tuesday#Member 1Member 2Member 3Project ideaPresentation 1Birna Íris Jónsdóttir Helgi Páll Helgason Ólafur Gíslason Agent Jerry (life simulator) TUESFriday#Member 1Member 2Member 3Project ideaPresentation 1Snorri Jónsson

public:t-622-arti-09-1:lab_1_materials

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Lab 1 material: Introduction to Lisp * Lisp Tutorial * LispBox - easy one-install Lisp implementations, Locally:lispbox07.exe Lispbox-0.7-with-acl81_express.dmg (OS X 10.4 PPC) * Lisp cheat sheet (PS) [(PDF)] * More material for learning Lisp: * Lisp Primer - A tutorial * Practical Common Lisp - A freely available book on Lisp * Emacs reference card (PDF) To work through these exercises, refer to the above material for more information.

public:t-622-arti-09-1:lab_2_materials

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Lab 2 materials: Comparing Agent Programs In lab 2 we will finish lab 1 and write a new kind of agent program that maintains a state. * Start by getting the file agents2.lisp. This is largely the same file as we had for the last lab session, except some fixes to accommodate stateful agents, and code to run experiments.

public:t-622-arti-09-1:lab_3_materials

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Lab 3 materials: Comparing Agent Programs + A* Search In lab 3 we will continue with lab 2 and also take a closer look at the A* Search algorithm using some testing tools. Examples and Tutorials for Pathfinding * There are many resources available for studying A* in the domain of pathfinding. Here are a few that you can take a quick look at now and then come back to them later when you want to implement something yourself.

public:t-622-arti-09-1:lab_4_materials

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Lab 4 materials - formulating search problems In lab 4 we will look at some problems from the textbook and formulate them as search problems. Group work We will start by splitting the class into four groups. Each group should formulate the following problems as search problems by giving an initial state, the goal test, successor function and cost function. You don't need to write any code, but describe these things precisely enough so that they could be implemented. You will have 15-20 minute…

public:t-622-arti-09-1:lab_9_materials

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Lab 9 materials In this session we will look at some basic Bayesian networks. We will do a few on the whiteboard and projector, using the Bayesian Network simulator available here: * Afterwards you will solve two problems in groups of 2-3, using the applet above. The problems are the following:

public:t-622-arti-09-1:lab_9_treasure

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Bayesian Inference: The Pirate Treasure You are a seasoned tomb raider and have spent the last week rummaging through an old pirate cove full of treasure. So far you have opened 100 chests and of those, 50 have in fact contained treasure! Out of these 50, 40 were trapped and you sustained some painful damage from opening them. Out of these 40 trapped chests, 28 were also locked. Now, of the 10 untrapped chests, three were locked. One would think that only chests with treasure would be trapped…

public:t-622-arti-09-1:main

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-622-ARTI, Introduction to Artificial Intelligence, Spring 2009 Basic Info * Instructor: Hannes Högni Vilhjálmsson (hannes+ru.is, skuggavera+hotmail.com on MSN) * Assistant: Arnar Birgisson (arnarbi+gmail.com also on GTalk) * Office: 2nd floor, Kringlan 1, 559-6323, 824-8814

public:t-622-arti-09-1:program_1

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Programming Assignment 1: Blind Search in LISP Weight: 5% Due: Monday, February 9th, by 23:59 Group Size: 1-2 Programming Language: LISP Introduction LISP is the second oldest high-level programming language and was the leading language in AI research from its infancy. It has greatly influenced other languages and computer science in general, for example by pioneering the

public:t-622-arti-09-1:program_2

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Programming Assignment 2: Game Playing Weight: 5% Due: Monday, March 2nd, by 23:59 Group Size: 1-2 Programming Language: The skeleton is in Java, but you can do this in any language Provided skeleton: Introduction [The board in "Connect 4" where red has just won] Having the computer play a game with a human player has always been an attractive way to showcase artificial intelligence, though one could argue that the intelligence used for choosing a good move in a particular game is too r…