Artificial Life and Robotics最新文献_第9页

Cellular automata model that generates hierarchical forms by simple operations between neighboring elements 通过相邻元素之间的简单操作生成层次结构的元胞自动机模型

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Artificial Life and Robotics Pub Date : 2025-08-12 DOI: 10.1007/s10015-025-01053-x

Takeshi Ishida

{"title":"Cellular automata model that generates hierarchical forms by simple operations between neighboring elements","authors":"Takeshi Ishida","doi":"10.1007/s10015-025-01053-x","DOIUrl":"10.1007/s10015-025-01053-x","url":null,"abstract":"<div><p>The phenomenon of self-organization, where structures spontaneously form without external instruction, is ubiquitous in nature and holds immense potential for engineering fields. However, elucidating the self-organizing mechanisms behind the complex, hierarchical structures seen in biological organisms remains a critical challenge. This study addresses this by proposing a hierarchical extension of the Ishida model, a two-dimensional cellular automaton (CA), to generate complex forms through simple, localized interactions between neighboring elements. The model employs a multi-level hierarchical structure where transition rules are applied sequentially to each layer, often with a time lag, to promote stable pattern formation and prevent unintended side effects. By adjusting a small set of core parameters (notably <i>w</i><sub><i>1</i></sub> and <i>w</i><sub><i>2</i></sub>), the model successfully generated a variety of static and dynamic hierarchical patterns. Specifically, it first produced a double-ring structure, which was then internally segmented into patterns with two, four, or six divisions. Furthermore, using an asymmetric initial configuration, the model generated dynamic patterns that maintained their shape while in motion, as well as forms with controlled, elongating protrusions. These results demonstrate that simple, iterative operations can create diverse, complex morphologies, offering a valuable framework for synthetic morphology and potential applications in fields like modular swarm robotics.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"30 4","pages":"658 - 677"},"PeriodicalIF":0.8,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529536","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

Pre-training Deep Neural Networks Using 3D Formula-Driven Supervised Learning for COPD Staging 使用3D公式驱动的监督学习预训练深度神经网络用于COPD分期

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Artificial Life and Robotics Pub Date : 2025-08-07 DOI: 10.1007/s10015-025-01051-z

Yasumasa Tamura, Kohei Harada, Wataru Noguchi, Kaoruko Shimizu, Satoshi Konno, Masahito Yamamoto

引用次数: 0

The information structure of boredom via integrated information theory 通过综合信息论研究无聊的信息结构

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Artificial Life and Robotics Pub Date : 2025-08-07 DOI: 10.1007/s10015-025-01050-0

Takayuki Niizato, Yuta Nishiyma, Shusaku Nomura

{"title":"The information structure of boredom via integrated information theory","authors":"Takayuki Niizato, Yuta Nishiyma, Shusaku Nomura","doi":"10.1007/s10015-025-01050-0","DOIUrl":"10.1007/s10015-025-01050-0","url":null,"abstract":"<div><p>Boredom is a complex psychological state, often seen as a double-edged sword. It can promote creativity, but is also linked to negative effects, such as irritability, fatigue, and even self-directed aggression. To better understand the neural underpinnings of boredom, this study applies Integrated Information Theory (IIT) to investigate how brain–body interactions reflect this state. Using electroencephalography (EEG) and autonomic measures (electrodermal activity and electrocardiography), we examined participants engaged in arithmetic tasks of varying difficulty levels. Our findings reveal that system integration, quantified by integrated information (<span>(Phi)</span>), increased during both easy and difficult tasks compared to the moderate condition. In contrast, the dynamical properties of the main complex—a core subset within IIT—showed an opposite trend, indicating improved body–brain coupling specifically during moderate tasks. Moreover, analyses using Earth Mover’s Distance revealed significant shifts in the main complex’s distribution during moderate tasks, whilst there were minimal changes under the easy condition. Interestingly, subjective reports indicated that irritation and tiredness were linked to transitions in the main complex, whilst boredom showed no correlation with <span>(Phi)</span>. These results suggest that boredom may emerge from a decoupling between brain and body systems, despite heightened system integration. Conversely, stronger body–brain coupling—characteristic of the moderate task condition—may buffer against subjective stress. This research highlights the potential of IIT for quantifying internal states like boredom and emphasises the need for further studies with larger, more diverse samples to validate and generalise these findings.\u0000</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"30 4","pages":"636 - 642"},"PeriodicalIF":0.8,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529651","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

Power steering control for compensating bicycle dynamics variation due to front basket loading 动力转向控制补偿前车筐载荷引起的自行车动力学变化

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Artificial Life and Robotics Pub Date : 2025-07-26 DOI: 10.1007/s10015-025-01043-z

Takaatsu Kihara, Yuzuki Sugasawa, Keigo Kuriyama, Masami Iwase

{"title":"Power steering control for compensating bicycle dynamics variation due to front basket loading","authors":"Takaatsu Kihara, Yuzuki Sugasawa, Keigo Kuriyama, Masami Iwase","doi":"10.1007/s10015-025-01043-z","DOIUrl":"10.1007/s10015-025-01043-z","url":null,"abstract":"<div><p>In this study, we focus on the realization of a power steering control that recovers the maneuverability of the bicycle which is deteriorated due to loading baggage in the front basket, by assisting the handlebar operation. According to the analysis of the effect of loading children and baggage in the front basket on maneuverability, it is found that the cause is an increase in the moment of inertia around the handlebar axis and a change in the position of the center of gravity. To solve the issue, previous studies have proposed a power steering mechanism that applies an assist torque proportional to the user’s steering torque to the handlebar axis. This mechanism has been shown to recover reduced maneuverability. However, when a rider rides a bicycle, the rider does not only operate the handlebars but also tilts the bicycle in the roll direction. Therefore, in this study, to propose a control method to assist the steering torque of the handlebar, a mathematical model of the bicycle is considered that includes both handlebar operation and bicycle tilt. To verify the effectiveness of the proposed model, we develop an electrically power assisted bicycle with the power steering mechanism and implement an assist algorithm. The experimental results confirmed that the proposed method is effective in assisting bicyclists with luggage in the front basket of their bicycles. </p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"30 4","pages":"603 - 612"},"PeriodicalIF":0.8,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529562","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

AI-driven enhancement of EEG-based detection of neurocognitive disorders 基于脑电图的神经认知障碍检测的ai驱动增强

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Artificial Life and Robotics Pub Date : 2025-07-21 DOI: 10.1007/s10015-025-01046-w

Kusum Tara, Ruimin Wang, Yoshitaka Matsuda, Satoru Goto, Takako Mitsudo, Takao Yamasaki, Takenao Sugi

{"title":"AI-driven enhancement of EEG-based detection of neurocognitive disorders","authors":"Kusum Tara, Ruimin Wang, Yoshitaka Matsuda, Satoru Goto, Takako Mitsudo, Takao Yamasaki, Takenao Sugi","doi":"10.1007/s10015-025-01046-w","DOIUrl":"10.1007/s10015-025-01046-w","url":null,"abstract":"<div><p>Early detection and accurate diagnosis of neurocognitive disorders (NCDs) are essential for enabling timely interventions to slow disease progression, preserve cognitive function, and enhance quality of life. This study introduces an EEG-based classification framework utilizing four AI-driven deep learning models—ResNet50-V2, EfficientNetB0, NasNetMobile, and MobileNetV2—to classify four neurocognitive groups: healthy controls (HC), mild cognitive impairment (MCI), Alzheimer’s disease (AD), and epilepsy (Ep) under eyes-closed (EC) conditions. To reduce complexity and improve accuracy, Fisher’s score was used to select 16 significant EEG channels from frontal, parietal, occipital, temporal, and central regions. Phase-amplitude coupling (PAC) images were generated from EC EEG signals to capture cross-frequency interactions, specifically how delta (0.5–4Hz) and theta (4–8Hz) phase modulate alpha (8–12Hz) and beta (12–35Hz) amplitudes—revealing functional brain connectivity. HC exhibited strong delta-alpha and reduced theta-beta coupling, while MCI and AD showed weakened delta-alpha and increased theta-beta interactions, reflecting cognitive decline. In contrast, Ep displayed elevated delta-alpha and reduced delta-beta coupling, linked to neural hyperexcitability. Among all models, MobileNetV2 achieved the best performance with 98.25% accuracy and 98.40% F score, attributed to its lightweight design and effective image feature extraction. This study’s novelty lies in its PAC image-based approach for NCD classification using MobileNetV2, providing valuable insights into non-linear hemispheric dynamics related to cognitive decline.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"30 4","pages":"613 - 621"},"PeriodicalIF":0.8,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529670","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

MonoDGAE: depth-guided attention and bilateral filtering for robust monocular 3D object detection MonoDGAE：用于鲁棒单目3D目标检测的深度引导注意力和双边滤波

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Artificial Life and Robotics Pub Date : 2025-07-20 DOI: 10.1007/s10015-025-01048-8

George Albert Bitwire, Samuel Kakuba, Dae Woong Cha, Dong Seog Han

{"title":"MonoDGAE: depth-guided attention and bilateral filtering for robust monocular 3D object detection","authors":"George Albert Bitwire, Samuel Kakuba, Dae Woong Cha, Dong Seog Han","doi":"10.1007/s10015-025-01048-8","DOIUrl":"10.1007/s10015-025-01048-8","url":null,"abstract":"<div><p>Robust monocular 3D object detection remains a pivotal challenge for intelligent robotic systems due to the absence of explicit depth information in single RGB images. In this paper, we propose a novel depth-guided attention enhancement (DGAE) module, integrated into the MonoDTR framework, to address its limitations in handling noisy depth supervision and refining spatial inconsistencies. DGAE leverages coarse depth maps as attention priors to guide visual feature refinement through temperature-scaled softmax and Gaussian smoothing, enabling enhanced spatial reasoning and robustness in cluttered scenes. To support this attention mechanism, we generate high-quality depth maps by projecting LiDAR points into the image plane and interpolating missing regions using a nearest-neighbor approach, followed by bilateral filtering and block downsampling to preserve edge details while reducing noise. This depth estimation pipeline improves the quality and coherence of the fused features used by DGAE. Extensive experiments on the KITTI 3D object detection benchmark show that our approach achieves state-of-the-art performance in moderate and hard detection scenarios for cars, pedestrians, and cyclists, while maintaining real-time inference speeds. These results underscore the effectiveness and practicality of our DGAE module for real-world 3D perception in autonomous driving applications.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"30 4","pages":"555 - 566"},"PeriodicalIF":0.8,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529563","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

Development of artificial muscles formed from shape memory alloys and elastomers based on dynamics analysis of walking and application to musculoskeletal humanoid legs 基于行走动力学分析的形状记忆合金和弹性体人造肌肉的研制及其在肌肉骨骼类人腿上的应用

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Artificial Life and Robotics Pub Date : 2025-07-19 DOI: 10.1007/s10015-025-01044-y

Yugo Kokubun, Kentaro Yamazaki, Ginjiro Takashi, Tatsumi Goto, Ontatsu Haku, Fumio Uchikoba, Minami Kaneko

{"title":"Development of artificial muscles formed from shape memory alloys and elastomers based on dynamics analysis of walking and application to musculoskeletal humanoid legs","authors":"Yugo Kokubun, Kentaro Yamazaki, Ginjiro Takashi, Tatsumi Goto, Ontatsu Haku, Fumio Uchikoba, Minami Kaneko","doi":"10.1007/s10015-025-01044-y","DOIUrl":"10.1007/s10015-025-01044-y","url":null,"abstract":"<div><p>Most humanoid robots use high-performance CPUs to process huge amounts of numerical calculations at high speed and control joint angles with servomotors. Humans, on the other hand, use neural networks to generate signals to contract and relax multiple muscles for efficient joint movement. We have created a musculoskeletal humanoid model that mimics the human musculoskeletal structure and have conducted dynamics analysis of walking. In the analysis, we obtained the time-specific generated force and contraction displacement of 12 different muscles during one walking cycle. In this study, based on dynamics analysis, artificial muscles were fabricated using elastomers and shape memory alloys for a total of 12 muscles: gluteus maximus, iliopsoas, rectus femoris, long head of biceps femoris, short head, vastus medialis and lateralis, gastrocnemius medialis and lateralis, tibialis anterior, and soleus muscles, and attached to the legs of a musculoskeletal humanoid. Using electrical signals from an external power source, the artificial muscles were driven based on the timing of muscle contraction during one cycle of walking, and the motion of the hip, knee, and ankle joints was reproduced in a stationary system. To validate the parameters of the artificial muscles obtained from the dynamics analysis of walking, the leg movements of the musculoskeletal humanoid were compared with the simulation results from the forward dynamics analysis.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"30 4","pages":"622 - 635"},"PeriodicalIF":0.8,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529605","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

Simulation of phototactic and puddle-crossing behaviors: a step toward assembling swarm logic gates using soldier crabs 光致性和水坑穿越行为的模拟：向使用兵蟹组装群体逻辑门迈出的一步

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Artificial Life and Robotics Pub Date : 2025-07-19 DOI: 10.1007/s10015-025-01047-9

Yuta Nishiyama, Kyohei Sagawa, Hisashi Murakami, Claudio Feliciani, Davin Browner, Andrew Adamatzky

{"title":"Simulation of phototactic and puddle-crossing behaviors: a step toward assembling swarm logic gates using soldier crabs","authors":"Yuta Nishiyama, Kyohei Sagawa, Hisashi Murakami, Claudio Feliciani, Davin Browner, Andrew Adamatzky","doi":"10.1007/s10015-025-01047-9","DOIUrl":"10.1007/s10015-025-01047-9","url":null,"abstract":"<div><p>Living organisms have been expected to realize an emergent computing. Although a wide variety of biological systems has been exploited as computing devices, there have been a few attempts of computing devices employing animal collective behaviors. Previous studies have implemented collision-based logical gates employing swarms of soldier crabs, <i>Mictyris guinotae</i>. However, how to control their movements in connected multiple gates has yet to be proposed. This study focused on their characteristic behaviors, a positive phototaxis and a puddle-crossing, as a mechanism by which they would autonomously adapt the group size at the joint part of the assembled gates. We performed simulation with the mutual anticipation model, where agents interact with each other based on potential transitions. The model successfully reproduced these behaviors by adjusting environmental factors. We propose how to use them for interconnections between logic gates and discuss its significance in terms of cognitive interaction.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"31 1","pages":"113 - 118"},"PeriodicalIF":0.8,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10015-025-01047-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147340368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Task-oriented adaptive learning of robot manipulation skills 面向任务的机器人操作技能自适应学习

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Artificial Life and Robotics Pub Date : 2025-07-18 DOI: 10.1007/s10015-025-01036-y

Kexin Jin, Guohui Tian, Bin Huang, Yongcheng Cui, Xiaoyu Zheng

{"title":"Task-oriented adaptive learning of robot manipulation skills","authors":"Kexin Jin, Guohui Tian, Bin Huang, Yongcheng Cui, Xiaoyu Zheng","doi":"10.1007/s10015-025-01036-y","DOIUrl":"10.1007/s10015-025-01036-y","url":null,"abstract":"<div><p>In industrial environments, robots are confronted with constantly changing working conditions and manipulation tasks. Traditional approaches that require robots to learn skills from scratch for new tasks are often slow and heavily dependent on human intervention. To address inefficiency and enhance robots’ adaptability, we propose a general Intelligent Transfer System (ITS) that enables autonomous and rapid new skill learning in dynamic environments. ITS integrates Large Language Models (LLMs) with Transfer Reinforcement Learning (TRL), harnessing both the advanced comprehension and generative capabilities of LLMs and the pre-acquired skill knowledge of robotic systems. First, to enable robots to comprehend unseen task commands and learn skills autonomously, we propose a reward function generation method based on task-specific reward components. This approach improves time efficiency and accuracy while eliminating the need for manual design. Secondly, to accelerate the learning speed of new robotic skills, we propose an Intelligent Transfer Network (ITN) within the ITS. Unlike traditional methods that merely reuse or adapt existing skills, ITN intelligently integrates related skill features, enhancing learning efficiency through knowledge fusion. We evaluate our method in simulation, demonstrating that our method enables the system to learn skills autonomously without pre-programmed behaviors, achieving 72.22% and 65.17% faster learning speeds for two major tasks compared to learning from scratch. Supplementary materials are accessible via our project page<i>:</i>https://jkx-yy.github.io/</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"30 4","pages":"567 - 576"},"PeriodicalIF":0.8,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529560","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

Generalization performance of reservoir computing implemented by asynchronously tuned elementary cellular automaton on parity task 异步调谐初等元胞自动机在奇偶性任务上实现储层计算的泛化性能

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Artificial Life and Robotics Pub Date : 2025-07-18 DOI: 10.1007/s10015-025-01045-x

Kota Nakada, Kengo Takahashi, Daisuke Uragami, Ramon Alonso-Sanz, Andrew Adamatzky, Yuta Nishiyama

{"title":"Generalization performance of reservoir computing implemented by asynchronously tuned elementary cellular automaton on parity task","authors":"Kota Nakada, Kengo Takahashi, Daisuke Uragami, Ramon Alonso-Sanz, Andrew Adamatzky, Yuta Nishiyama","doi":"10.1007/s10015-025-01045-x","DOIUrl":"10.1007/s10015-025-01045-x","url":null,"abstract":"<div><p>Reservoir computing (RC) is a computer architecture allowing us to utilize any nonlinear dynamical system as a computing device called a reservoir. Exploiting elementary cellular automata (ECAs) as reservoirs is no exception. Recent studies have shown that the RC implemented by asynchronously tuned ECAs (AT_ECAs) has an advantage of enhancing the learning ability to identify multiple patterns, suggesting effects of critical spacetime patterns that the AT_ECAs create in a wide range of transition rules. However, the generalization capability of the AT_ECA-based RC remains unclear. This study evaluated the generalization performance of the AT_ECA-based RC using the temporal parity task in comparison with the ECA-based RC. We found that the AT_ECA-based RC demonstrated higher performance than ECA-based RC in most rules. This might have been a result of critical behaviors that the AT_ECAs universally generate with different mechanisms from the ECAs.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"31 1","pages":"77 - 82"},"PeriodicalIF":0.8,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10015-025-01045-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147340084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0