International Journal of Smart Computing and Artificial Intelligence最新文献_第2页

The Effect of Speculative Computation on Combinatorial Optimization Problems 推测计算对组合优化问题的影响

International Journal of Smart Computing and Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.52731/ijscai.v3.i2.374

Yasuki Iizuka, Akira Hamada, Yosuke Suzuki

引用次数: 0

Dynamic Travel Permits Allocation Mechanism for Decreasing Traffic Congestion and Drivers’ Dissatisfaction 减少交通拥堵和驾驶员不满的动态出行许可分配机制

International Journal of Smart Computing and Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.52731/ijscai.v6.i2.734

Yuka Yamanari, Takashi Nishino, Hisashi Hayashi

引用次数: 0

An Ensemble Learning Method of Adaptive Structural Deep Belief Network for AffectNet 一种面向AffectNet的自适应结构深度信念网络集成学习方法

International Journal of Smart Computing and Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.52731/ijscai.v6.i1.640

T. Ichimura, Shin Kamada

引用次数: 1

Task Decomposition and Role Sharing for Real-time Human-AI Swarm Collaboration 面向实时人机群协作的任务分解与角色共享

International Journal of Smart Computing and Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.52731/ijscai.v5.i1.637

S. Karakama, Natsuki Matsunami, Masayuki Ito

{"title":"Task Decomposition and Role Sharing for Real-time Human-AI Swarm Collaboration","authors":"S. Karakama, Natsuki Matsunami, Masayuki Ito","doi":"10.52731/ijscai.v5.i1.637","DOIUrl":"https://doi.org/10.52731/ijscai.v5.i1.637","url":null,"abstract":"In spite of the impressive advances in artificial intelligence (AI), close collaboration between humans and AI systems is still difficult to achieve. To overcome this problem, we designed AI agents with a behavior tree that enables us to know what they are trying to do, and by using a consensus building algorithm, that is, a contract net protocol, a human and a group of AI agents were put together as one team. Taking advantage of this architecture, we designed an approach to decomposing cooperative tasks into appropriate roles. The effectiveness and feasibility of this approach were evaluated with teams in a simulated Tail Tag game. Matches were held with up to 29 AI agents and 1 person on one team and 30 people on the other team. The results indicate that our approach works almost evenly with human-human collaboration by sharing roles be-tween a human and AI swarm. By understanding the roles of AI agents, a person can immediately understand the role that he/she should take. For further improvement, we also identified that it is necessary for a person to be able to give concise and global instructions.","PeriodicalId":179818,"journal":{"name":"International Journal of Smart Computing and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123630579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integration Framework of Monocular Vision-Based Drivable Region Detection and Contour-Based Vehicle Localization for Autonomous Driving Systems 基于单目视觉的自动驾驶区域检测与基于轮廓的车辆定位集成框架

International Journal of Smart Computing and Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.52731/ijscai.v3.i2.369

Feng‐Li Lian, Jia-En Lee, Hou-Tsan Lee

{"title":"Integration Framework of Monocular Vision-Based Drivable Region Detection and Contour-Based Vehicle Localization for Autonomous Driving Systems","authors":"Feng‐Li Lian, Jia-En Lee, Hou-Tsan Lee","doi":"10.52731/ijscai.v3.i2.369","DOIUrl":"https://doi.org/10.52731/ijscai.v3.i2.369","url":null,"abstract":"Perception and localization are the keys in autonomous vehicle systems and driver assistance systems. The perception provides the information of environments around the vehicle, like other vehicles, pedestrians, and road signs. The localization provides the position and heading of vehicle, which can be used for path planning, navigation. With perception and localization process, the safety of vehicle driving could be increased. In this paper, an image segmentation method called region growing, using threshold estimated from previous indicated road region, is proposed to determine that the pixels in the image belong to road region or not. With a defined initial partial road region, the whole road region can be obtained. On the other hand, with a prior birdeye view map of the area where the vehicle drives, the contours of road region extracted from captured images are matching with the contour on the map by iterative closest point to obtain the vehicle position. In addition, in order to increase the precision of matching, the movements of camera are also estimated by matching the contour in consecutive frames. Furthermore, the position estimated from visual information integrated with the information from GPS to obtain more accurate position. Comparing with vision-based localization only, the integration with GPS reduces the weight and influence of bad matching results, which make the estimated position more accurate. The experimental results show that in structured road, with the localization by road signs, stop lines, and lane lines, the global positions of vehicle can be estimated while the relative movements are very close to GPS data.","PeriodicalId":179818,"journal":{"name":"International Journal of Smart Computing and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125797877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reduction of Variables through Nearest Neighbor Relations in Threshold Networks 阈值网络中基于最近邻关系的变量约简

International Journal of Smart Computing and Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.52731/ijscai.v4.i1.510

N. Ishii, K. Iwata, Kazuya Odagiri, Toyoshiro Nakashima, T. Matsuo

引用次数: 0

Automatic comment generation for source code using external information by neural networks for computational thinking 利用神经网络计算思维的外部信息自动生成源代码注释

International Journal of Smart Computing and Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.52731/ijscai.v4.i2.572

Hiromitsu Shiina, Sakuei Onishi, Akiyoshi Takahashi, Nobuyuki Kobayashi

引用次数: 1

constrained recursion algorithm for tree-structured LSTM with mini-batch SGD 基于小批量SGD的树结构LSTM约束递归算法

International Journal of Smart Computing and Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.52731/ijscai.v7.i1.669

R. Ando, Yoshiyasu Takefuji

引用次数: 0

Extraction of Genes and Transcripts Associated with Liver Cancer Using Machine Learning 利用机器学习提取与肝癌相关的基因和转录本

International Journal of Smart Computing and Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.52731/ijscai.v6.i1.628

Koshiro Sekine, T. Hochin, Hiroki Nomiya, H. Yoshida

引用次数: 0

Realization for Finger Character Recognition Method by Similarity Measure of Finger Features 基于手指特征相似性度量的手指字符识别方法的实现

International Journal of Smart Computing and Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.52731/ijscai.v6.i1.684

Takuma Nitta, Shinpei Hagimoto, Ari Yanase, Ryotaro Okada, Virach Sornlertlamvanich, T. Nakanishi

引用次数: 2