- Prof. Dancy's Site - Course Site -

Bucknell CSCI 357 - Introduction to AI & Cognitive Science, Spring 2021

Introduction to Artificial Intelligence and Cognitive Science: Building Artificial Minds

Prof. Christopher L. Dancy
Office: Dana 340
Phone: 570.577.1907
Office Hours: By appointment My calendar
Tentative Course Schedule - Check here periodically for changes

Skip to the course overview

Before we get to more course info

Student Mental Health Statement and Resources

In this classroom and on Bucknell’s campus we support mental health efforts. Any student who is struggling and believes this may impact your performance in the course is encouraged to contact your Associate Academic Dean or the Dean of Students at 570-577-1601 for support. Furthermore, please approach me if you are comfortable in doing so. This will enable me to provide resources and support. If immediate mental health assistance is needed, call the Counseling & Student Development Center at 570-577-1604 (24/7).

Resource Links:

Students with disabilities

Any student who needs an accommodation based on the impact of a disability should contact the OAR at OAR@bucknell.edu; 570-577-1188 or complete the Disability Accommodation Request form (https://bucknell-accommodate.symplicity.com/public_accommodation/). The OAR will coordinate reasonable accommodations for students with documented disabilities.

Religious Holidays

Accommodations for religious holidays can be made, send a request and we'll talk about it.

Basic Needs Security

Any student who has difficulty affording groceries or accessing sufficient and nutritious food to eat every day, or who lacks a safe and stable place to live, and believes it is affecting their learning, is urged to contact the Dean of Students for support. Furthermore, I encourage you to notify me of this as well - I will keep all such information confidential. This will enable me to provide any resources that I may possess and identify other resources in the University.

Academic Responsibility

Bucknell University Honor Code

As a student and citizen of the Bucknell University community:

  1. I will not lie, cheat or steal in my academic endeavors.
  2. I will forthrightly oppose each and every instance of academic dishonesty.
  3. I will let my conscience guide my decision to communicate directly with any person or persons I believe to have been dishonest in academic work.
  4. I will let my conscience guide my decision on reporting breaches of academic integrity to the appropriate faculty or deans.

Course Overview

How can we build artificial minds? What do we need to represent and how do we represent it? How can we make them learn, and perceive in an environment? How can we use the way people think to design these minds? What about the environment, how should it affect an intelligent agent? How do societal and sociocultural structures provide foundations for the AI systems we create, deploy, and integrate?

In this course, I will give you some tools to provide some answers to these questions. Ultimately, as with most endeavors this difficult, we will come up short. But fear not! You will have an opportunity to explore past answers to these questions and learn from them. Furthermore you will have an opportunity to use the thinking, techniques, and tools you learn in this course and in the future!

This course will not provide full coverage of AI and Cognitive Science for this would almost certainly be impossible given the time! These fields are big with many theories, subfields, and applications. This course will focus on a balance between philosophical, historical, cognitive, and methodological aspects of AI. (Though, thankfully no one will create anything close to the Ava in "Ex Machina"!)

A big part of the course will involve cohorts each of which will focus on one of four topics:

What does it mean to critically think about the ways in which AI systems are designed, developed, and deployed in our society?

What are Neural Networks? How can I implement them? How might I use it?

What are some perspectives in Cognitive Science? What are Cognitive Systems? What are Cognitive Architectures

We'll also have some weeks where everyone covers the same topics:

Course Outcomes

  1. Students will be able to explain the fundamentals of some AI & Cognitive Science tools and techniques, and implement an technique/tool used to build intelligent agents.
  2. Students will understand some of the historical perspectives of AI and how it relates to Cognitive Science and be able to think critically about these perspectives
  3. Students will understand what agents and models are, particularly as they apply to building artificial minds
  4. Students will have a better appreciation for the process of writing a scientific style report that accompanies a software implementation of a technique/algorithm/theory, especially as it relates to Cognitive Science.

Locations for Course Information

Readings

There will be a wide variety of readings assigned throughout the semester. Some readings will be from a specific text (Mind Design or Sciences of the Articial), many others will be made available online. You are expected to complete any assigned reading by the specified due date. Be prepared to discuss the reading material in class. You will occasionally be required to complete short answers to questions related to the readings, or offer reflective, critical, short essays related to the topic of interest. The assignment itself will contain instructions on how to submit your answers.
**It is important that you complete the assigned readings. Groups will be discussing and reflecting upon those readings and as we complete our midterm and final projects, it will be important for you to be able to think about the project in the context of readings you might have completed (depending on your cohort)

Grading

Category Weight
Midterm Project 15%
Final Project 30%
Assignments 20%
Class Discussion Notes 5%
Cohort Presentation 5%
Quizzes 20%
Journal 5%

Midterm Project (15%)

There will be one midterm project to be completed this semester. The project will have two phases. Each phase is due by 11:00 PM on the due date. Late projects will receive a 10% penalty each day they are overdue. The final phase of the project will include a group presentation. This project is meant to give you a mid-semester opportunity to explore the things we've learned and try to implement something you might find interesting. It will also allow you to see what ideas others have come up with and see how you might want to borrow (and CITE!) their ideas for a final project.

Final Project (30%)

There will be one final project during the semester. The project willn have three major phases. Each phase is due by 11:00 PM on the due date. Late projects will receive a 10% penalty each day they are overdue. The final phase of the project will include a group presentation and a final paper/report at the end of the semester during the final exam slot.

Assignments (20%)

Each cohort will have assignments for that specific cohort and deliverables. You should follow the particular schedule for your cohort. Information on grading for assignments will be contained within those assignments

Discussion questions (2%)

2% of the 20% will go to a grade for providing at least two discussion questions for each lecture based on the readings of that particular day.

Class discussion notes (5%)

A note taker (assigned by Prof. Dancy each class) will take notes on the discussion within cohorts and between the whole class. They will have to record their comments on a common google doc (they can paste their comments to the document later).

Cohort presentations (5%)

Each cohort (as a group) will present on their topic on a Friday. I'm not looking for anything ground-breaking here, I'm just interested in seeing the weeks information from your eyes (and I believe the class will benefit from the multiple perspectives.) A signup sheet is posted that will detail eligible weeks for note takers.
The presentation should be on something new that relates to what we've talked about in class (within your cohort). I would prefer you discuss a scholarly article (i.e., peer-reviewed), but if you find a news article that you think fits really well, ask me (it might be good enough, but I need to vet it).

Quizzes (20%)

There will be quizzes given at random points throughout the semester. Generally, no announcement will be given related to the quizzes. The quizzes will be will be given during the scheduled lecture time via gradescope.

Make-up / Missed Quiz Policy

Make-ups for quizzes will be considered on a case by case basis. If you miss a quiz and aren't approved for a make-up, you receive a 0 for that quiz. Your lowest quiz grade will be dropped from your final grade.

Journal (5%)

You will be required to make a weekly journal entry on Moodle. You must create one entry every week, and only one entry. You cannot make up entries if you forget. If you do, they will not be counted toward your journal grade. Your journal entry should contain the following information:

Late / Missed Journal Policy

It is up to you to complete each entry in a timely manner. You will not be reminded. You cannot make up any missed journal entries.

Important Disclaimer

The instructors promise the best effort in adhering to the above rules but reserve the right to change them if deemed necessary. For instance, slight alterations to the course schedule are possible if the class needs more/less time for a certain topic; additional readings may be assigned during the semester as needed; and so on. Updates will be announced in class and by email, posted on course webpage and on Google Classroom. Check your Bucknell email and Google Classroom at least daily.