【摘要】：游戲系統(tǒng)中智能代理擔負著與玩家直接進行情感交互的重任,它的決策系統(tǒng)作為游戲可玩性的技術核心體現(xiàn)著“人工智能”的技術成果,直接關系著游戲設計的成敗。但是當前主流的被市場廣泛認可的智能代理決策系統(tǒng)都是基于預制邏輯進行搭建的,它們自身的動態(tài)調整能力有限,比較容易被玩家找出破綻從而降低決策智能,進而影響用戶體驗。而采用傳統(tǒng)人工智能技術的智能代理決策系統(tǒng),雖然能提供自主的決策智能,但是由于比較占用系統(tǒng)計算能力并且使用限制較多等原因,并不能被市場廣泛認可。因此一種能繼承傳統(tǒng)決策系統(tǒng)的傳統(tǒng)優(yōu)勢,同時又能結合新型人工智能技術,根據(jù)游戲運行情況進行實時、自主地動態(tài)調整的決策系統(tǒng)的研發(fā)變得尤為重要。本文對當前主流和新型的智能代理決策系統(tǒng):模糊邏輯、人工神經網(wǎng)絡、遺傳算法、游戲腳本、有限狀態(tài)機、行為樹進行了介紹和分析。針對傳統(tǒng)智能代理決策系統(tǒng)存在的不能很好的在實際使用環(huán)境中保持決策合理性,無法有效適配玩家多樣化操作的問題,本文提出了一種基于機器學習ID3算法與行為樹的ID3行為樹作為智能代理的決策系統(tǒng)。它通過收集玩家與NPC交互時產生的后臺數(shù)據(jù)借由ID3算法的分析指導行為樹進行決策,實時調節(jié)決策系統(tǒng),保持決策的合理性。為驗證新決策系統(tǒng)的有效性,基于Unity3d平臺設計了一款采用此方案的NPC智能代理,最后搭建了游戲系統(tǒng)并對其進行了實驗,實驗結果驗證了此方案的有效性。
[Abstract]:The intelligent agent in the game system undertakes the important task of directly interacting with the players. As the technical core of the playability of the game, its decision-making system embodies the technical achievements of "artificial intelligence", which is directly related to the success or failure of the game design. However, the current mainstream intelligent agent decision-making systems, which are widely recognized by the market, are built based on prefabricated logic, and their own dynamic adjustment ability is limited, so it is easier for players to find out the flaws and reduce the decision intelligence. And then affect the user experience. Although the intelligent agent decision system based on traditional artificial intelligence technology can provide independent decision intelligence, it can not be widely recognized by the market because it occupies the computing power of the system and has more restrictions. Therefore, it is particularly important to develop a decision system which can inherit the traditional advantages of the traditional decision system and combine the new artificial intelligence technology to carry out real time and independently dynamic adjustment according to the operation of the game. In this paper, the mainstream and new intelligent agent decision systems, such as fuzzy logic, artificial neural network, genetic algorithm, game script, finite state machine and behavior tree, are introduced and analyzed. In view of the problem that the traditional intelligent agent decision system can not maintain the rationality of decision in the actual use environment and can not effectively adapt to the diversified operation of players, In this paper, a ID3 behavior tree based on machine learning ID3 algorithm and behavior tree is proposed as an intelligent agent decision system. By collecting the background data generated by the interaction between players and NPC, it guides the behavior tree to make decisions through the analysis of ID3 algorithm, adjusts the decision system in real time, and maintains the rationality of the decision. In order to verify the effectiveness of the new decision system, a NPC intelligent agent based on Unity3d platform is designed. Finally, the game system is built and its experiments are carried out. The experimental results verify the effectiveness of the scheme.
【學位授予單位】：合肥工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP18

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本文編號：2486367