Class Policies
Prerequisites
- CS 325 (Algorithms)
- Knowledge of Java programming
- The ability to take simple derivatives
- Note: CS 381 (Programming Language Fundamentals) is listed as a prequisite but is not needed
Accommodations
Students with documented disabilities who may need accommodations, who have any emergency medical information the instructor should be aware of, or who need special arrangements in the event of evacuation, should make an appointment with the instructor as early as possible, and no later than the first week of the term. Class materials will be made available in accessible format upon request.
Grading and Exams
An approximate weighting of the marks in the course is listed below. This may change slightly depending on the number
and size of the assignments.
- Programming Assignments (3 of them) - 24%
- Written Assignments (4 of them) - 16%
- Midterm - 20%
- Final - 40%
The midterm and exam are are open-book. Do not rely too heavy on your notes during an exam! Use them as a safety net.
Policy on collaboration
In solo assignments, collaboration is limited to verbal discussion of general approaches and strategies for the
assignment. You can give each other examples that are not in the assignment. If you collaborate in this way, you
will be asked to declare your collaborators.
Things not allowed:
- No use of code, documentation, or other written media from sources other than yourself (eg. classmates, internet, etc. ) unless explicitly allowed by the assignment.
- Do not tell each other the answers
For assignments done in teams, team members within the same team may explicitly discuss answers. However, the rules above apply between teams.
For further details, please refer to the OSU Academic dishonesty policy and the
CS Academic dishonesty policy.
Late Policy
Assignments are due at the start of class. The late policy is as follows:
- 0-24 hours late: 90% of the final score
- 24-48 hours late: 50% of the final score
- After 48 hours late: 0%
If you hand in a late written assignment, please slip the assignment under my office door (KEC 2075).
Blackboard
I will use Blackboard for two purposes in this course:
- Storing and distributing your grades. Let us know if there are any mistakes in your grades. Please check them after each assignment and exam.
- Discussion board. If you have questions about assignments or exams, the following options are available:
- See the instructor or TA during their office hours.
- Post to the discussion board. You will find that the discussion board has a much better response time than email because many more
pairs of eyes will be monitoring it. You will get help from the instructor, the TA, and even other students.
- If you're really stuck, email the TA or the instructor. If you send the instructor email, be warned that he receives well over
a hundred email messages a day and he may not get to your email for a while.
Learning Objectives
- Analyze the dimensions along which agents and environments vary, along with key functions that must be implemented in a general agent.
- Implement agents using search algorithms such as uninformed search, informed search or local search.
- Develop strategies for agents in games of perfect and imperfect information.
- Represent knowledge of the world using logic and infer new facts from that knowledge.
- Use a Bayesian network to make quantitative (probabilistic) and qualitative inferences.
- Implement a Bayesian network that solves a simple version of a problem such as text categorization or object recognition.
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