Course | CMPT 310 D100 |
---|---|
Semester | Summer 2012 |
Title | Artificial Intelligence Survey |
Campus | Burnaby Campus |
Instructor(s) | Steven Pearce <stevenp@sfu.ca> |
TA(s) | Sitanshu Gakkhar <sgakkhar@sfu.ca> |
Criteria | criteria.pdf |
Students(s) |
David Carlson, Davie Ching, Mark Lauman, Christopher Kwong |
Topic
Advanced Learning Agent Analysis
Abstract
We will be presenting an advanced topic on a learning agent implementation; by specifically focusing on the agent’s implementation by way of neural networks and genetic algorithms. Our goal is to provide the class with a tangible example of how neural networks can be implemented and how to artificially simulate learning with a defined environment. The presentation will consist of a demonstration of the problem domain, analysis of the neural network and genetic algorithm implementations, and will culminate in critical analysis of the base example. Within the critical analysis, we hope to simulate changes to the problem domain in the form of manipulating the neural network architecture (ie. increase/decrease number of neurons within the network) and externally controlling the environment (ie. limit goal availability).
Our base case example upon which our analysis and implementation will be upon can be found at: http://site.nixuz.com/evolving-fish-intelligence
Project Submission
Resource | Contents | Description | Filetype |
---|---|---|---|
Presentation | Presentation | Presentation used in class. | Powerpoint (*.pptx) |
Analysis | Code | Analysis of the source code. | Acrobat (*.pdf) |
Graphs | Analysis of the fish over time. | Acrobat (*.pdf) | |
Program | 1x6 (Original) | 1 row, 6 columns network. Version used in base case. | Webpage (*.html) |
2x6 | 2 rows, 6 columns network | Webpage (*.html) | |
3x2 | 3 rows, 2 columns network | Webpage (*.html) | |
6x1 | 6 rows, 1 column network | Webpage (*.html) | |
6x6 | 6 rows, 6 columns network | Webpage (*.html) | |
11x24 | 11 rows, 24 columns network. Processor intensive! | Webpage (*.html) |