Tencent's New AI Method Outperforms Larger Systems in Strategic Games
Tencent researchers have made a significant breakthrough in AI strategic thinking. They've developed a new training method, using the popular game Honor of Kings, that enables smaller AI systems to outperform larger ones in decision-making. Meanwhile, Google has launched the 'Game Arena', an open platform for AI models to compete using real game behavior as a benchmark.
Traditional AI agents can act in games but lack the ability to explain their decisions. Conversely, language models can analyze strategies but struggle with practical implementation. Tencent's new framework, Think in Games (TiG), bridges this gap. It allows AI systems to learn and execute complex macro-actions in games, such as attacking or retreating, with remarkable success.
In a recent experiment, AI agents were trained to perform 40 different macro-actions in Honor of Kings. The results were impressive: smaller AI systems, trained with this method, outperformed larger models in strategic decision-making. This method builds on the success of the ROCKET-1 project, which demonstrated a hierarchical agent solving simple tasks in Minecraft with a 100% success rate using real game behavior as a data source.
Tencent's Think in Games framework is a significant step forward in AI strategic thinking. By enabling AI systems to learn and execute complex strategies in games, it brings us closer to AI agents that can make informed decisions and explain their reasoning. The launch of Google's 'Game Arena' provides an exciting platform for further development and benchmarking of these frontier AI models.
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