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Adapting Reinforcement Learning to Tetris
| Content Provider | Semantic Scholar |
|---|---|
| Author | Carr, Donald |
| Copyright Year | 2005 |
| Abstract | This paper discusses the application of reinforcement learning to Tetris. Tetris and reinforcement learning are both introduced and defined, and relevent research is discussed. An agent based on existing research is implemented and investigated. A reduced representation of the Tetris state space is then developed, and several new agents are implemented around this state space. The implemented agents all display successful learning, and show proficiency within certain conditions. ACM Classification System (1998) I.2.8 Problem Solving, Control Methods, and Search |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.cs.ru.ac.za/research/g02c0108/files/finalwriteuphandin.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |