Name
Abstract | ||
|---|---|---|
It has been well recognized that human makes use of both declarative memory and procedural memory for decision making and problem solving. In this paper, we propose a computational model with the overall architecture and individual processes for realizing the interaction between the declarative and procedural memory based on self-organizing neural networks. We formalize two major types of memory interactions and show how each of them can be embedded into autonomous reinforcement learning agents. Our experiments based on the Toad and Frog puzzle and a strategic game known as Starcraft Broodwar have shown that the cooperative interaction between declarative knowledge and procedural skills can lead to significant improvement in task performance. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.5555/2615731.2617530 | AAMAS |
Keywords | DocType | Citations |
declarative knowledge,declarative memory,frog puzzle,declarative-procedural memory interaction,starcraft broodwar,autonomous reinforcement,memory interaction,cooperative interaction,procedural memory,computational model,procedural skill | Conference | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenwen Wang | 1 | 46 | 3.61 |
| Ah-Hwee Tan | 2 | 1385 | 112.07 |
| Loo-Nin Teow | 3 | 103 | 17.29 |
| Yuan Sin Tan | 4 | 36 | 5.74 |