| Course ID: | CSCI 8920. 4 hours. |
| Course Title: | Decision Making Under Uncertainty |
Course
Description: | Choosing optimally among different lines of actions is a key
aspect of autonomy in artificial agents. This course will focus
on how to make optimal and approximately optimal decisions in
single and multiagent settings. It will be self-contained,
introducing background literature such as aspects of
probability and game theories. |
| Oasis Title: | DECISION MAKING |
| Prerequisite: | CSCI 4470/6470 or permission of department. |
Semester Course
Offered: | Not offered on a regular basis. |
| Grading System: | A-F (Traditional) |
|
| Course Objectives: | 1. To study algorithms for automated decision making by
agents situated in uncertain single-agent and multiagent
environments
2. To understand key subareas of artificial intelligence,
economics and cognitive psychology
3. To become proficient in the use of computing tools
related to decision making, and designing and giving
presentations effectively |
| Topical Outline: | I. Introduction
a. Requirements for decision models and solutions
b. Probability theory background
c. Bayesian networks and Influence diagrams
II. Decision making in single agent setting
a. Markov decision processes (MDP)
b. Partially observable Markov decision processes (POMDP)
c. Dynamic influence diagrams
d. Psychology of decision making
III. Decision making in multiagent setting
a. Game theory background
b. Repeated strategic and Bayesian games
c. Decentralized MDPs
d. Partially observable Dec-MDPs (Dec-POMDPs) and
approximations
e. Interactive POMDPs (I-POMDPs) and approximations
f. Interactive Influence diagrams |