Center for Analysis and Design of Intelligent Agents public:t-622-arti-11-1

public:t-622-arti-11-1:final_project

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

Final Projects, Spring 2011

public:t-622-arti-11-1:lab_1_materials

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

Lab 1: Introduction to Lisp * Material: * The history of Lisp written by its author John McCarthy (interesting read) * Lisp Tutorial: Part I, Part II and Part III. * Lisp cheat sheet: (PS Format) or ([PDF Format]). * More material for learning Lisp: * Another Tutorial: Lisp Primer. * A freely available book on Lisp:

public:t-622-arti-11-1:lab_2_materials

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

Lab 2: Comparing Agent Programs In this lab session we will finish lab 1 and write a new kind of agent program mantaining a state. * Getting Started: Start by getting the file [agents2.zip] and unzipping it into your working directory. This is largely the same file as we had for the last lab session, except some fixes to accommodate agents having a state, and code to run experiments.

public:t-622-arti-11-1:lab_3_materials

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

Lab 3: Braitenberg Vehicles Material * Braitenberg Vehicles from Wikipedia; * Valentino Braitenberg's book: Vehicles Experiments in synthetic Psychology (In PDF format); * Braitenberg Vehicle simulator: * Link to the Java Applet; * Applet Commands; * Vehicle's Model Description. Before you Start * Through the next steps you are going to change several settings into the

public:t-622-arti-11-1:lab_4_materials

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

Lab 4: A* Pathfinding Search In this lab we will take a closer look at the A* Search algorithm using some Testing Tools and different Heuristics for the Pathfinding problem. Material 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-11-1:lab_5_materials

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

Lab 5: Formulating Search Problems In this lab we will look at some real world problems and formulate them as Search Problems. Group work We will start by splitting the class into several groups. Each group should formulate the following problems (all) as

public:t-622-arti-11-1:lab_6_materials

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

Lab 6: PowerLoom In this lab we will work with First Order Logic and PowerLoom, a knowledge representation system. You will have to go through the following steps and create some logical statements representing Family Relations. PowerLoom * The main webpage of

public:t-622-arti-11-1:lab_7_materials

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

Lab 7: Bayesian Networks In this session we will look at some basic Bayesian Networks and you will solve two problems using a Bayesian Network simulator. Material The following is a Java applet for Bayesian Network simulations: * Problem 1: Smelly Doors

public:t-622-arti-11-1:lab_7_treasure_hunt

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-11-1:main

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

T-622-ARTI, Introduction to Artificial Intelligence, Spring 2011 Basic Info * Instructor: Hannes Högni Vilhjálmsson (hannes+ru.is, skuggavera+hotmail.com on MSN) * Assistant: Angelo Cafaro (angelo08+ru.is) * Office: 2nd floor, Venus, 559-6323, 824-8814 * Theory Lectures:

public:t-622-arti-11-1:program_1

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

Programming Assignment 1: Implementing Blind Search Weight: 5% Due: Thursday, February 10th, by 23:59 Group Size: 1-2 Programming Language: LISP or Another Language of your choice 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-11-1:program_2

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

Programming Assignment 2: Game Playing Weight: 5% Due: Thursday, March 3rd, by 23:59 Group Size: 1-3 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…