• 제목/요약/키워드: Reinforcement Value

검색결과 458건 처리시간 0.026초

강화 학습에 기반한 뉴럴-퍼지 제어기 (Neural-Fuzzy Controller Based on Reinforcement Learning)

  • 박영철;김대수;심귀보
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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    • pp.245-248
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    • 2000
  • 본 논문에서는 강화 학습 개념을 도입하여 자율이동 로봇의 성능을 개선하고자 한다. 본 논문에서 사용되는 시스템은 크게 두 부분으로 나눌 수가 있다. 즉, 뉴럴 퍼지 부분과 동적귀환 신경회로망이다. 뉴럴 퍼지 부분은 로봇의 다음 행동을 결정하는 부분이다. 또한 동적귀환 신경회로망으로부터 내부 강화 신호를 받아 학습을 하여 최적의 행동을 결정하게 된다. 동적 귀환신경회로망은 환경으로부터 외부 강화신호를 입력으로 받아 뉴럴 퍼지의 행동결정에 대해 평가를 한다. 또한 내부강화 신호 값을 결정하는 동적 귀환 신경회로망의 웨이트는 유전자 알고리즘에 의해 진화를 한다. 제안한 알고리즘 구조를 컴퓨터 시뮬레이션상에서 자율 이동 로봇의 제어에 적용을 함으로서 그 유효성을 증명하고자 한다.

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수중운동체의 롤 제어를 위한 Deep Deterministic Policy Gradient 기반 강화학습 (Reinforcement Learning based on Deep Deterministic Policy Gradient for Roll Control of Underwater Vehicle)

  • 김수용;황연걸;문성웅
    • 한국군사과학기술학회지
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    • 제24권5호
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    • pp.558-568
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    • 2021
  • The existing underwater vehicle controller design is applied by linearizing the nonlinear dynamics model to a specific motion section. Since the linear controller has unstable control performance in a transient state, various studies have been conducted to overcome this problem. Recently, there have been studies to improve the control performance in the transient state by using reinforcement learning. Reinforcement learning can be largely divided into value-based reinforcement learning and policy-based reinforcement learning. In this paper, we propose the roll controller of underwater vehicle based on Deep Deterministic Policy Gradient(DDPG) that learns the control policy and can show stable control performance in various situations and environments. The performance of the proposed DDPG based roll controller was verified through simulation and compared with the existing PID and DQN with Normalized Advantage Functions based roll controllers.

스마트 TMD 제어를 위한 강화학습 알고리즘 성능 검토 (Performance Evaluation of Reinforcement Learning Algorithm for Control of Smart TMD)

  • 강주원;김현수
    • 한국공간구조학회논문집
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    • 제21권2호
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    • pp.41-48
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    • 2021
  • A smart tuned mass damper (TMD) is widely studied for seismic response reduction of various structures. Control algorithm is the most important factor for control performance of a smart TMD. This study used a Deep Deterministic Policy Gradient (DDPG) among reinforcement learning techniques to develop a control algorithm for a smart TMD. A magnetorheological (MR) damper was used to make the smart TMD. A single mass model with the smart TMD was employed to make a reinforcement learning environment. Time history analysis simulations of the example structure subject to artificial seismic load were performed in the reinforcement learning process. Critic of policy network and actor of value network for DDPG agent were constructed. The action of DDPG agent was selected as the command voltage sent to the MR damper. Reward for the DDPG action was calculated by using displacement and velocity responses of the main mass. Groundhook control algorithm was used as a comparative control algorithm. After 10,000 episode training of the DDPG agent model with proper hyper-parameters, the semi-active control algorithm for control of seismic responses of the example structure with the smart TMD was developed. The simulation results presented that the developed DDPG model can provide effective control algorithms for smart TMD for reduction of seismic responses.

고속도로 자율주행 시 보상을 최대화하기 위한 강화 학습 활성화 함수 비교 (Comparison of Reinforcement Learning Activation Functions to Maximize Rewards in Autonomous Highway Driving)

  • 이동철
    • 한국인터넷방송통신학회논문지
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    • 제22권5호
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    • pp.63-68
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    • 2022
  • 자율주행 기술은 최근 심층 강화학습의 도입으로 큰 발전을 이루고 있다. 심층 강화 학습을 효과적으로 사용하기 위해서는 적절한 활성화 함수를 선택하는 것이 중요하다. 그 동안 많은 활성화 함수가 제시되었으나 적용할 환경에 따라 다른 성능을 보여주었다. 본 논문은 고속도로에서 자율주행을 학습하기 위해 강화 학습을 사용할 때 어떤 활성화 함수를 사용하는 것이 효과적인지 12개의 활성화 함수 성능을 비교 평가한다. 이를 위한 성능 평가 방법을 제시하였고 각 활성화 함수의 평균 보상 값을 비교하였다. 그 결과 GELU를 사용할 경우 가장 높은 평균 보상을 얻을 수 있었으며 SiLU는 가장 낮은 성능을 보여주었다. 두 활성화 함수의 평균 보상 차이는 20%였다.

휨과 전단을 고려한 철근콘크리트 방호벽 성능에 관한 연구 (Bending and Shear Capacity of Reinforced Concrete Protective Wall)

  • 권영범;박종일
    • 한국안전학회지
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    • 제38권2호
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    • pp.44-51
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    • 2023
  • With the recent increase in gas energy use, risk management for explosion accidents has been emphasized. Protective walls can be used to reduce damage from explosions. The KOSHA GUIDE D-65-2018 suggests the minimum thickness and height of protective walls, minimum reinforcement diameter, and maximum spacing of reinforcements for the structural safety of the protective walls. However, no related evidence has been presented. In this study, the blast load carrying capacity of the protective wall was analyzed by the pressure-impulse diagrams while changing the yield strength of the reinforcement, concrete compressive strength, reinforcement ratio, protective wall height, and thickness, to check the adequacy of the KOSHA GUIDE. Results show that failure may occur even with design based on the criteria presented by KOSHA GUIDE. In order to achieve structural safety of protective walls, additional criteria for minimum reinforcement yield strength and maximum height of protective wall are suggested for inclusion in KOSHA GUIDE. Moreover, the existing value for minimum reinforcement ratio and the thickness of the protective wall should be increased.

실내모형시험을 통한 지반혼합 및 주입공법의 노후저수지 차수 보강성능 비교 연구 (A Comparative Study on the Impermeability-reinforcement Performance of Old Reservoir from Injection and Deep Mixing Method through Laboratory Model Test)

  • 송상훤
    • 한국농촌건축학회논문집
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    • 제24권2호
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    • pp.45-52
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    • 2022
  • Of the 17,106 domestic reservoirs(as of December 2020), 14,611 are older than 50 years, and these old reservoirs will gradually increase over time. The injection grouting method is most applied to the reinforcement method of the aging reservoir. However, the injection grouting method is not accurate in uniformity and reinforced area. An laboratory model test was conducted to evaluate the applicability of the deep mixing method, which compensated for these shortcomings, as a reservoir reinforcement method. As a result of calculating the hydraulic conductiveity for each method through the model test results, the injection grouting method was calculated as a hydraulic conductiveity value that was about 7.5 times larger than that of the deep mixing method. As a result of measuring the water level change in the laboratory model test, it was found that the water level change decreased in the injection method and deep mixing method compared to the non-reinforcement method. In addition, deep mixing method showed a water level change of about 15% based on 40 hours compared to the injection method, indicating that the water-reducing effect was superior to that of the injection method.

A Motivation-Based Action-Selection-Mechanism Involving Reinforcement Learning

  • Lee, Sang-Hoon;Suh, Il-Hong;Kwon, Woo-Young
    • International Journal of Control, Automation, and Systems
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    • 제6권6호
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    • pp.904-914
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    • 2008
  • An action-selection-mechanism(ASM) has been proposed to work as a fully connected finite state machine to deal with sequential behaviors as well as to allow a state in the task program to migrate to any state in the task, in which a primitive node in association with a state and its transitional conditions can be easily inserted/deleted. Also, such a primitive node can be learned by a shortest path-finding-based reinforcement learning technique. Specifically, we define a behavioral motivation as having state-dependent value as a primitive node for action selection, and then sequentially construct a network of behavioral motivations in such a way that the value of a parent node is allowed to flow into a child node by a releasing mechanism. A vertical path in a network represents a behavioral sequence. Here, such a tree for our proposed ASM can be newly generated and/or updated whenever a new behavior sequence is learned. To show the validity of our proposed ASM, experimental results of a mobile robot performing the task of pushing- a- box-in to- a-goal(PBIG) will be illustrated.

Real-Time Application의 효과적인 QoS 라우팅을 위한 적응적 Route 선택 강화 방법 (Reinforcement Method to Enhance Adaptive Route Search for Efficient Real-Time Application Specific QoS Routing)

  • Oh, Jae-Seuk;Bae, Sung-Il;Ahn, Jin-Ho;Sungh Kang
    • 대한전자공학회논문지TC
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    • 제40권12호
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    • pp.71-82
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    • 2003
  • 본 논문은 real-time 어플리케이션들을 위한 보나 효과적이고 효율적으로 ant-like mobile agent들이 QoS metrics를 고려하여 네트워크상에서 목적지까지 가장 최적화된 route을 찾는 Ant 알고리듬을 바탕으로 한 QoS 라우팅 알고리듬에서의 route 선택 강화 계산방법을 제시한다. 시뮬레이션 결과 본 논문에서 제시하는 방법이 기존의 방법보다 delay jitter와 bandwidth를 우선으로 하는 real-time application에 대한 가장 최적화된 route을 보다 효과적이고 보다 네트워크 환경에 적응적으로 찾아내는 것을 확인하였다.

고성능 철근콘크리트 보의 휨강도 및 연성능력에 관한 실험적 연구 (An Experimental Study on the Flexural Strength and Ductility Capacity of Reinforced High Performance Concrete Beams)

  • 김용부;고만영;김상우
    • 한국콘크리트학회:학술대회논문집
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    • 한국콘크리트학회 1998년도 가을 학술발표논문집(II)
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    • pp.501-506
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    • 1998
  • This paper is an experimental study on the flexural strength and ductility capacity of reinforced high performance concrete beams with the concrete which has compressive strength of 600~700kg/$\textrm{cm}^2$, slump value of 20~25cm and slump-flow value of 60~70cm. Total 8 beams with different tensile reinforcement ratio and pattern of loading were tested. Form the results of reinforced high performance concrete beams, the equivalent stress block parameters proposed by MacGregor et al. or New Zealand code are recommended to use. Also, an extreme fiber concrete compressive strain of reinforced high performance concrete beams are distributed 0.0033~0.0048. In reinforced high performance concrete beams, reinforcement ratio in order to insure curvature ductility index 2 and 4 propose by ACI code should be less than those of reinforced normal strength concrete beams.

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벽 및 천장이 흡음재로 마감된 다목적 체육관에서 음원종류에 따른 실내음향특성의 분석 (Analysis of the Room Acoustic Characteristics depending on the Sound Sources for a Multi-purpose Gymnasium finished with Absorbers on Walls and Ceiling)

  • 박현구;전지현;송혁;김선우
    • KIEAE Journal
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    • 제2권1호
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    • pp.41-48
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    • 2002
  • This study aims to investigate and evaluate the room acoustic designs of a multi purpose gymnasiums which do not use adjustable treatments in order to change the acoustical characteristics. Considering the main uses of gymnasium and auditorium, experiments were carried out using both nondirectional speakers on the stage and loudspeaker installed on the ceiling. The result from the study are as follows; Measured RT under unoccupied condition was a little longer than the expected value, therefore, in the case of occupied condition RT would be close to the optimum value. However, parameters that evaluate intelligibility and speech transmission property appeared to be low and have large differences depending on the measuring points, therefore, more effective sound reflecting surfaces and sound reinforcement systems should be considered.