티스토리 뷰

Natural Language Processing / Conversational Behavior


Beyond Finite State Machines: Managing Complex, Intermixing Behavior Hierarchies

/Michael Mateas (Georgia Institute of Technology) and Andrew Stern (InteractiveStory.net)
Game Developers Conference, 2004.
Abstract: This lecture discusses the design and implementation idioms for structuring complex, hierarchical, character behavior. This includes idioms for authoring tightly coordinated multi-character behavior, such as conversation behavior. Techniques include the use of meta- behaviors to monitor and modify the execution state of other behaviors, and the use of joint behaviors to manage multi-character coordination (avoiding ad hoc communication). Finally, advantages and challenges of moving away from imperative programming (C++) to behavioral programming are discussed.


A Flexible Tagging System for AI Resource Selection
(AI 자원 선택을 위한 유연한 꼬리표 시스템)

/
Paul Tozour (Retro Studios)
AI Game Programming Wisdom 2, 2003.

Topics: Architecture, NLP; Genres: General
Abstract:
게임 AI 에이전트가 플레이어와 의사소통하는 수단은 두 가지이다. 하나는 애니메이션이고, 또하나는 음성이다. 즉 에이전트는 움직이고 말을 할 수 있다.

물론 이는 상황을 너무 단순화한 것이다. 게임 AI 캐릭터는 게임 세계의 물체들과도 상호작용하며, 절차적 애니메이션 같은 기법을 사용하면 캐릭터가 움직이는 방식을 매우 유연하게 제어할 수 있다. 그러나 근복적으로 게임 AI 에이전트가 플레이어에게 자신을 표현하는 기본 수단은 소리와 움직임이다.

이 글은 AI 에이전트가 실행할 자원을 선택하는 문제에 대한 것이다. 이 글에서 설명하는 시스템은 AI 코드와 내부적인 자원 시스템 사이의 인터페이스 역할을 한다. 이러한 시스템은 완전히 일반적인 방식에서 고도로 특화된 방식까지 임의의 수준에서 설꼐와 AI 관련 자원들을 지정하고 사용할 수 있게 한다. 이 시스템은 기본적으로 사운드와 애니메이션의 선택을 염두에 둔 것이지만, 다른 용도로도 사용 할 수 있다.

읽다보니 자연어 처리를 위한 형태소 분석시 Tagging 하고 부분이랑 유사하다는 생각이든다.  
또 결과에 대한 모호성을 없에기 위한 방법과 비슷한 의사결정 트리도 보인다.

SAPI: An Introduction to Speech Recognition

/James Matthews (Generation5)
AI Game Programming Wisdom 2, 2003.
Topics: NLP; Genres: General
Abstract: This article looks at providing newcomers to SAPI an easy-to-follow breakdown of how to get a simple SAPI application working. It looks briefly at setting up SAPI, how to construct the XML grammar files, handling SAPI messages and using the SAPI text-to-speech functionality. All these concepts are tied together using an demonstration application designed to make learning SAPI simple yet entertaining.

Microsoft SAPI (Speech Application Programming Interface)
음성인식 ( Speech Recognition, SR )
음성합성 ( Text-to-Speech, TTS )

SAPI: Extending the Basics

/James Matthews (Generation5)
AI Game Programming Wisdom 2, 2003.
Topics: NLP; Genres: General
Abstract: This article extends upon the previous one by discussing concepts like dynamic grammar, additional XML grammar tags, altering voices and more SAPI events. The chapter uses a simple implementation of Go Fish! to demonstrate the concepts presented.

Conversational Agents: Creating Natural Dialogue between Players and Non-Player Characters
대화형 에이전트: 플레이와 NPC 사이의 자연스러운 대화 만들기

/Penny Drennan (School of ITEE, University of Queensland)
AI Game Programming Wisdom 2, 2003.
Topics: NLP; Genres: General
Abstract: The quality of interactions between non-player characters (NPCs) and the player is an important area of Artificial Intelligence in games that is still in need of improvement. Game players frequently express that they want to see opponents and NPCs that appear to possess intelligence in games. However, most dialogue between players and NPCs in computer games is currently scripted, which does not add to the appearance of intelligence in the NPC. This article addresses these problems by giving an overview of NPCs in current games and presents a method called conversational agents, for improving dialogue between players and NPCs. Conversational agents are software agents that consist of models of personality and emotion, which allow them to demonstrate believable conversational behavior. The advantages of conversational agents include their ability to portray emotions and personality through dialogue. However, they also have disadvantage, in that they can be time consuming to develop.

This article will begin by discussing the conversational behavior of NPCs in current games. We will not be looking at the artificial intelligence (AI) capabilities of NPCs, only their ability to interact with the player. We will then discuss the components of a conversational agent - how to give it the appearance of personality and emotion. We will also look at the input that the agent needs to get from the environment, and what we want the agent to say to the player. We will conclude with the advantages and disadvantages of using conversational agents in games.

Screaming at the Machine: Using Speech Recognition as a Complement to Traditional Game Input Technique
Dave Bartolomeo (Microsoft)
Game Developers Conference Proceedings, 2003.
Topics: NLP; Genres: General
Abstract: Advances in speech recognition technology, gigahertz CPUs, and the offloading of graphics processing to the GPU have made it practical to use speech recognition in commercial-quality games. The characteristics of speech recognition make it a unique input device, significantly different from a mouse, keyboard, or joystick. Speech is more flexible than keyboard commands, easier to use than multi-level menus, and it enables players to issue commands without moving their focus away from the primary game interface. This talk demonstrates how to incorporate speech recognition into your game in a way that complements traditional input devices, rather than trying to replace them.

Practical Natural Language Learning

/Jonty Barnes (Lionhead Studios), Jason Hutchens (Amristar)
AI Game Programming Wisdom, 2002.
Topics: Learning, NLP; Genres: General
Abstract: The perception of intelligence seems to be directly related to the observation of behavior that is surprising yet sensible. Natural language interfaces were common features of computer entertainment software prior to the advent of sophisticated computer graphics, but these were often repetitive in nature: encountering the same scripted conversation over and over again quickly becomes boring. Stochastic language models have the ability to acquire various features of a language from observations they make, and these features can be used generatively to produce novel utterances that have the properties of being both surprising and sensible. In this article we show how such a system, when used to host in-game socially-oriented conversations, can greatly contribute towards the subjective impression of intelligence experienced by the player.

Lies, Damn Lies, and ASR Statistics
Neil Kirby (Bell Labs)
Computer Game Developers Conference Proceedings, 1998.
Topics: NLP; Genres: General

Natural Language Processing in 55 Minutes or Less

John O'Neil
Computer Game Developers Conference Proceedings, 1998.
Topics: NLP; Genres: General

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살려고 생각은 안했었는데..사고야 말았다. AI Game Programming Wisdom 2
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책이 너무 두꺼워 뒤에 제목을 본문에서 찾는 것도 좀 걸린다. 책이 두꺼워서
그냥 지나쳤던 부분들인데.. 가이드를 해주니 도움이 된다. Good!

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