Player | Score | ELO |
---|---|---|
GLaDOS | 22.5 | 1821.741847219824 |
Ani Sun | 21.0 | 1781.8601657517233 |
Bottie 2.0 | 21.0 | 1777.8853844131195 |
SELECT * | 20.5 | 1759.0785418587327 |
b71d452f-fe9d-4445-9146-8de30f11eae1 | 19.5 | 1741.0961145016745 |
GOAT BOT | 18.0 | 1707.925401439686 |
JINX bot | 17.5 | 1697.1980992425877 |
DFS | 17.5 | 1691.986989700273 |
Dub Bot | 17.0 | 1692.032894554528 |
stephen_curry_GOAT_pg | 17.0 | 1689.765318087451 |
Box Theory | 17.0 | 1685.7231986427316 |
Alita: Battle Angel | 17.0 | 1678.561578831914 |
Edited by WILL SHORTZ | 16.5 | 1669.640588625867 |
PentaKill | 16.0 | 1655.5092554255984 |
flynn.eth | 15.5 | 1646.063966456729 |
ZaleX++ | 15.0 | 1629.0842887384924 |
315T | 14.5 | 1621.6518630724793 |
Thayer St. Motorcycle | 14.5 | 1619.9062049326242 |
no lecture no problem | 13.0 | 1589.621241752766 |
GJ | 12.5 | 1582.9486569632847 |
SLATER | 11.5 | 1544.4291225236962 |
wholeLottaRed | 8.5 | 1478.0172204231976 |
AvengingKnight | 4.0 | 1377.2511586518754 |
mregan6 | 4.0 | 1370.835806794842 |
Dreaming of Electric Sheep | 3.5 | 1363.3972044212383 |
bruh moment | 2.5 | 1338.0128386287922 |
code monkey knows all | 0.5 | 1297.491590371159 |
Terminator | 0.5 | 1297.2826530965738 |
CS1410 is an introductory course to the field of Artificial Intelligence, including knowledge representation and algorithms for search, optimization, planning, logical and probabilistic reasoning, and machine learning. We're gonna teach you how to teach computers common sense! Prerequisites to CS1410 include (CSCI 0160, 0180 or 0190) and (CSCI 0220, 1450, 0450, APMA 1650 or 1655) or minimum score of WAIVE in 'Graduate Student PreReq'. This course is taught by Professor George Konidaris. Students interested in taking CS1410 as a capstone course should email George at george_konidaris@brown.edu.
In person lectures take place Tuesdays and Thursdays from 1:00pm to 2:20pm eastern time. Lectures slides will be posted prior to each lecture. Recordings will be available for remote students and review, which are available on Panopto. The supplementary textbook for this course is Artificial Intelligence: A Modern Approach (Pearson Series in Artifical Intelligence)
Topic | Slides | Recordings | Readings |
---|---|---|---|
9/9 Introduction; Agents and Agenthood | link | ||
9/14 Search | link | ||
9/16 Game Theory | link | ||
9/21 Adversarial Search | link | ||
9/23 Knowledge Representation and Reasoning (Logic) | link | ||
9/28 Uncertain Knowledge and Bayes' Rule | link | ||
9/30 Bayesian Networks | link | ||
10/5 Hidden Markov Models | link | ||
10/7 Robot Motion Planning | link | ||
10/12 Classical Planning | link | ||
10/14 Probabilistic Planning | link | ||
10/19 Reinforcement Learning | link | ||
10/21 Reinforcement Learning II | link | ||
10/26 Supervised Learning | link | ||
10/28 Supervised Learning II | link | ||
11/2 Unsupervised Learning | link | ||
11/4 Unsupervised Learning II | |||
11/9 Natural Language Processing | link | ||
11/16 Natural Language Processing | |||
11/18 Robotics | |||
11/29 The Philosophy of AI |
All projects are in Python and due at 11:59pm Eastern on the listed date. Before each project (besides the install assignment) you have two opportunities to receive results from our hidden tests. For instance, if you submit your code for Search to the 'Search (First Submission)' assignment on Gradescope before the listed Submission 1 deadline, you will receive your grade from our autograder once the deadline passes (this includes both visible and hidden tests, though you will not be able to see what the hidden tests are). This is the same autograder that will be used on the Final Submission of the same project. The deadline for the written portion of each project is always one day after the final code deadline. You are granted 3 late days for all (not each) projects. Read more about the grading policy in the Resources section.
Project | Release | Submission 1 Due Date | Submission 2 Due Date | Final Code Due Date | Written Part Due Date |
---|---|---|---|---|---|
Install Assignment | Sept 9 | Sept 12 | N/A | Sept 14 | N/A |
Search | Sept 15 | Sept 20 | Sept 22 | Sept 24 | Sept 25 |
Adversarial Search | Sept 25 | Sept 29 | Oct 1 | Oct 4 | Oct 5 |
KRR | Oct 5 | Oct 7 | Oct 9 | Oct 13 | Oct 14 |
HMM | Oct 13 | Oct 21 | Oct 25 | Oct 29 | Oct 30 |
Reinforcement Learning | Oct 30 | Nov 4 | Nov 6 | Nov 8 | Nov 9 |
Supervised Learning | Nov 10 | N/A | N/A | Nov 22 | Nov 23 |
Tron | Oct 13 | TBD | TBD | Oct 18 | TBD |
Oct 13 | TBD | TBD | Nov 1 | TBD | |
Oct 13 | TBD | TBD | Nov 22 | TBD | |
Oct 13 | TBD | TBD | Dec 17 | TBD |
In person TA Hours are held at the CIT Room 205. TA Hours will be available for remote students, times TBD!
gdk@cs.brown.edu
cs1410headtas@lists.brown.edu