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Real-Time Transfer and Adaptive Learning Approach for Game Agents
Game agents(NPCs) should have the ability to react in cooperate, and have the ability to learn from mistakes and build up their own experience. In this paper, we describe a general approach for transfer learning and adaptive mechanism for game agents' real-time planning and learning system in which agents modify their behavior in response to changes of the PCs.
| Download Paper | |
| Full Title | Real-Time Transfer and Adaptive Learning Approach for Game Agents in a Layered Architecture |
| Year | 2009 |
| Language | English |
| Book | Intelligent Virtual Agents - IVA 2009 |
| Keywords | game agents, behavior, virtual agent |
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