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Title Generalising plans to influence landscapes for robust agent execution in virtual worlds / Luke Dicken.
Name Dicken, Luke. .
Abstract Artificial Intelligence is one of the most promising areas of modern technology, with great potential for changing the face of the modern world. However almost universally we use one of two paradigms in AI - either techniques that are very efficient but which lack good long-term reasoning, or techniques that are exceptionally good at providing long-term solutions but which are slow to execute and reasonably inflexible. This is a problem because the natural world does not decompose so neatly into one or other box, many situations require fast problem-solving that is also cognisant of long-term objectives and motivations.A great example of this kind of problem is frequently encountered in the video game industry, where the computational load is predominantly tied up simulating an environment and rendering this graphically to the player. As a consequence there is very limited processing power available for the AI systems that power the activity within that environment. However, there is also a need for the actions being taken by the agents in the game to at least appear to be intelligent, and for many games that intelligence needs to be exhibited in a dynamic, rapidly changing world. This is a clear example of an area where efficient long-term reasoning is necessitated, and cannot adequately be solved with either of the two existing families of algorithms. The core hypothesis of the work is derived from the need to bridge the gap between the two paradigms and states that an architecture that operates in this way "will be demonstrably more robust and efficient than those that are either purely Reactive or purely Deliberative." Additionally, as a technique intrinsically bound with an industrial need, it is also essential that any proposed architecture be viable in an industry setting.
Publication date 2016
Name University of Strathclyde. Dept. of Computer and Information Sciences.
Name University of Strathclyde. Dept. of Computer and Information Sciences. Strathclyde Artificial Intelligence and Games Research Group.
Thesis note Thesis PhD University of Strathclyde 2016 T14376
System Number 000004600

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