정보과학회 논문지 (Journal of KIISE)

  • 제42권3호
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  • Pages.320-327
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  • 2015
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  • 2383-630X(pISSN)
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  • 2383-6296(eISSN)
한국정보과학회 (Korean Institute of Information Scientists and Engineers)
권호 표지
DOI QR코드

DOI QR Code

모듈형 행동선택네트워크를 이용한 거울뉴런과 마음이론 기반의 의도대응 모델

An Intention-Response Model based on Mirror Neuron and Theory of Mind using Modular Behavior Selection Networks

  • 채유정 (연세대학교 컴퓨터과학과) ;
  • 조성배 (연세대학교 컴퓨터과학과)
  • 투고 : 2014.08.28
  • 심사 : 2014.12.30
  • 발행 : 2015.03.15
⟨ 이전 논문 다음 논문 ⟩

초록

최근 다양한 분야에 서비스 로봇이 상용화되고 있지만 대부분의 로봇 에이전트는 사용자의 구체적인 명령에 의존적이고, 불안정한 센서정보를 기반으로 환경변화에 빠르게 대응하여 목적을 달성하기는 어려운 문제가 있다. 이러한 문제를 해결하기 위해, 본 논문은 사람이 타인의 의도를 이해하고 대응하는 과정을 설명하는 거울뉴런(mirror neuron)과 마음이론(theory of mind) 시스템을 모델링하고 로봇에이전트에 적용하여 유용성을 입증한다. 제안하는 의도-대응 모델은 거울뉴런의 빠르고 직관적인 대응행동과 중간목적 지향적인 특성을 구현하기 위해, 환경과 목적을 고려하는 행동선택 네트워크(behavior selection network)를 사용한다. 또한, 장기적인 행동계획을 기반으로 대응행동을 수행하는 마음이론 시스템을 수행하기 위해, 계층적 계획생성 기법을 이용하여 중간목적 단위로 행동을 계획하고 이를 기반으로 행동선택네트워크 모듈을 제어한다. 다양한 시나리오에 대해 실험한 결과 외부자극에 적절한 대응행동이 생성됨을 확인하였다.

Although service robots in various fields are being commercialized, most of them have problems that depend on explicit commands by users and have difficulty to generate robust reactions of the robot in the unstable condition using insufficient sensor data. To solve these problems, we modeled mirror neuron and theory of mind systems, and applied them to a robot agent to show the usefulness. In order to implement quick and intuitive response of the mirror neuron, the proposed intention-response model utilized behavior selection networks considering external stimuli and a goal, and in order to perform reactions based on the long-term action plan of theory of mind system, we planned behaviors of the sub-goal unit using a hierarchical task network planning, and controled behavior selection network modules. Experiments with various scenarios revealed that appropriate reactions were generated according to external stimuli.

키워드

과제정보

연구 과제 주관 기관 : 한국연구재단

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