Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 8 of 8 for “"real-time strategy game"”.
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Developing game AI for the real‐time strategy game StarCraft
Research into intelligent agents designed to play Real-Time Strategy (RTS) games has been limited compared to the amount of research that has gone into designing agents for playing board games such as chess. This is largely due to the fact that developing an agent for RTS is more complicated. There …
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The effect of intermediate concepts in hierarchical relational learning
… Learner to learn target selection for a real-time strategy game and did cross-validation tests with varying levels of intermediate concept support. The results show that including intermediate concepts does not always improve performance and accuracy.
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Environmental curriculum learning for efficiently achieving superhuman play in games
… made large strides in training agents to play games, including complex ones such as arcade game Pommerman and real-time strategy game StarCraft II. To allow agents to grasp the many concepts in these games, curriculum learning has been used to teach agents multiple skills over time. We present …
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Grounding language in spatial routines
… to build a natural language interface to a real time strategy game, in which a player controls an army of units in a battle. The system understands the meaning of context-dependent natural language commands such as "Run back!" and "Move the marines on top above the fiamethrowers on the …
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Warm-Starting Networks for Sample-Efficient Continuous Adaptation to Parameter Perturbations in Multi-Agent Reinforcement Learning
… mastering challenging problems. Because many real-world systems involve multiple agents interacting with each other in a shared environment, one particularly active subfield of RL is multi-agent reinforcement learning (MARL). Learning robust multi-agent policies in real-time strategy games, …
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Efficient execution of fine-grained actors on multicore processors
… implement both static (compiler) and dynamic (runtime) techniques that overcome these perceived inefficiencies, while retaining key actor semantics, even in a framework setting. We compare the performance of ActorFoundry with other frameworks for small benchmarks and programs. The results suggest …
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Building Strategic AI Agents for Human-centric Multi-agent Systems
… while improving performance in the benchmark game of no-press Diplomacy. Then, we develop a procedure for modeling populations of agents that communicate with humans using natural language. Our sample-efficient multitask training scheme for latent language policies (LLPs) improves the reward …
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Validation of the recognition-primed decision model and the roles of common-sense strategies in an adversarial environment
… microworld, as an experimental platform, using a real time strategy (RTS) game called Rise of Nations (RON). The specific objectives of this dissertation were: 1.Contribute to the validation of recognition-primed decision (RPD) model in a simulated adversarial environment; 2.Explore the roles of …