scholarly journals Unifying Search-based and Compilation-based Approaches to Multi-agent Path Finding through Satisfiability Modulo Theories

2019 ◽  
Author(s):  
Pavel Surynek
Keyword(s):  
Undirected Graph ◽  
State Of The Art ◽  
The State ◽  
Satisfiability Modulo Theories ◽  
Path Finding ◽  
Low Level ◽  
Multi Agent ◽  
High Level ◽  
Novel Algorithm

We unify search-based and compilation-based approaches to multi-agent path finding (MAPF) through satisfiability modulo theories (SMT). The task in MAPF is to navigate agents in an undirected graph to given goal vertices so that they do not collide. We rephrase Conflict-Based Search (CBS), one of the state-of-the-art algorithms for optimal MAPF solving, in the terms of SMT. This idea combines SAT-based solving known from MDD-SAT, a SAT-based optimal MAPF solver, at the low-level with conflict elimination of CBS at the high-level. Where the standard CBS branches the search after a conflict, we refine the propositional model with a disjunctive constraint. Our novel algorithm called SMT-CBS hence does not branch at the high-level but incrementally extends the propositional model. We experimentally compare SMT-CBS with CBS, ICBS, and MDD-SAT.

scholarly journals Multi-Agent Path Finding for Large Agents

2019 ◽  
Vol 33 ◽  
pp. 7627-7634 ◽  
Author(s):  
Jiaoyang Li ◽  
Pavel Surynek ◽  
Ariel Felner ◽  
Hang Ma ◽  
T. K. Satish Kumar ◽  
...  
Keyword(s):  
Real World ◽  
State Of The Art ◽  
Tree Search ◽  
Multiple Constraints ◽  
Path Finding ◽  
Multiple Points ◽  
Admissible Heuristics ◽  
Single Location ◽  
Multi Agent ◽  
High Level

Multi-Agent Path Finding (MAPF) has been widely studied in the AI community. For example, Conflict-Based Search (CBS) is a state-of-the-art MAPF algorithm based on a twolevel tree-search. However, previous MAPF algorithms assume that an agent occupies only a single location at any given time, e.g., a single cell in a grid. This limits their applicability in many real-world domains that have geometric agents in lieu of point agents. Geometric agents are referred to as “large” agents because they can occupy multiple points at the same time. In this paper, we formalize and study LAMAPF, i.e., MAPF for large agents. We first show how CBS can be adapted to solve LA-MAPF. We then present a generalized version of CBS, called Multi-Constraint CBS (MCCBS), that adds multiple constraints (instead of one constraint) for an agent when it generates a high-level search node. We introduce three different approaches to choose such constraints as well as an approach to compute admissible heuristics for the high-level search. Experimental results show that all MC-CBS variants outperform CBS by up to three orders of magnitude in terms of runtime. The best variant also outperforms EPEA* (a state-of-the-art A*-based MAPF solver) in all cases and MDD-SAT (a state-of-the-art reduction-based MAPF solver) in some cases.

scholarly journals Exploring Large Virtual Environments by Thoughts Using a Brain–Computer Interface Based on Motor Imagery and High-Level Commands

2010 ◽  
Vol 19 (1) ◽  
pp. 54-70 ◽  
Author(s):  
Fabien Lotte ◽  
Aurélien van Langhenhove ◽  
Fabrice Lamarche ◽  
Thomas Ernest ◽  
Yann Renard ◽  
...  
Keyword(s):  
Virtual Environments ◽  
Motor Imagery ◽  
State Of The Art ◽  
Complex Interaction ◽  
The State ◽  
Virtual Museum ◽  
Interaction Technique ◽  
Low Level ◽  
Points Of Interest ◽  
High Level

Brain–computer interfaces (BCI) are interaction devices that enable users to send commands to a computer by using brain activity only. In this paper, we propose a new interaction technique to enable users to perform complex interaction tasks and to navigate within large virtual environments (VE) by using only a BCI based on imagined movements (motor imagery). This technique enables the user to send high-level mental commands, leaving the application in charge of most of the complex and tedious details of the interaction task. More precisely, it is based on points of interest and enables subjects to send only a few commands to the application in order to navigate from one point of interest to the other. Interestingly enough, the points of interest for a given VE can be generated automatically thanks to the processing of this VE geometry. As the navigation between two points of interest is also automatic, the proposed technique can be used to navigate efficiently by thoughts within any VE. The input of this interaction technique is a newly-designed self-paced BCI which enables the user to send three different commands based on motor imagery. This BCI is based on a fuzzy inference system with reject options. In order to evaluate the efficiency of the proposed interaction technique, we compared it with the state of the art method during a task of virtual museum exploration. The state of the art method uses low-level commands, which means that each mental state of the user is associated with a simple command such as turning left or moving forward in the VE. In contrast, our method based on high-level commands enables the user to simply select its destination, leaving the application performing the necessary movements to reach this destination. Our results showed that with our interaction technique, users can navigate within a virtual museum almost twice as fast as with low-level commands, and with nearly half the commands, meaning with less stress and more comfort for the user. This suggests that our technique enables efficient use of the limited capacity of current motor imagery-based BCI in order to perform complex interaction tasks in VE, opening the way to promising new applications.

scholarly journals Saliency Detection by Multilevel Deep Pyramid Model

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Hai Wang ◽  
Lei Dai ◽  
Yingfeng Cai ◽  
Long Chen ◽  
Yong Zhang
Keyword(s):  
Background Noise ◽  
State Of The Art ◽  
Saliency Detection ◽  
Saliency Map ◽  
Multiple Features ◽  
Low Level ◽  
Pyramid Model ◽  
High Level ◽  
Different Levels ◽  
Better Than

Traditional salient object detection models are divided into several classes based on low-level features and contrast between pixels. In this paper, we propose a model based on a multilevel deep pyramid (MLDP), which involves fusing multiple features on different levels. Firstly, the MLDP uses the original image as the input for a VGG16 model to extract high-level features and form an initial saliency map. Next, the MLDP further extracts high-level features to form a saliency map based on a deep pyramid. Then, the MLDP obtains the salient map fused with superpixels by extracting low-level features. After that, the MLDP applies background noise filtering to the saliency map fused with superpixels in order to filter out the interference of background noise and form a saliency map based on the foreground. Lastly, the MLDP combines the saliency map fused with the superpixels with the saliency map based on the foreground, which results in the final saliency map. The MLDP is not limited to low-level features while it fuses multiple features and achieves good results when extracting salient targets. As can be seen in our experiment section, the MLDP is better than the other 7 state-of-the-art models across three different public saliency datasets. Therefore, the MLDP has superiority and wide applicability in extraction of salient targets.

Masking Models and Watermarking

2011 ◽  
pp. 93-116
Author(s):  
Mirko Luca Lobina ◽  
Luigi Atzori ◽  
Davide Mula
Keyword(s):  
Signal Processing ◽  
Intellectual Property ◽  
State Of The Art ◽  
The State ◽  
Audio Watermarking ◽  
Digital Right Management ◽  
The Future ◽  
Psychological Models ◽  
High Level ◽  
The Relationship

Many audio watermarking techniques presented in the last years make use of masking and psychological models derived from signal processing. Such a basic idea is winning because it guarantees a high level of robustness and bandwidth of the watermark as well as fidelity of the watermarked signal. This chapter first describes the relationship between digital right management, intellectual property, and use of watermarking techniques. Then, the crossing use of watermarking and masking models is detailed, providing schemes, examples, and references. Finally, the authors present two strategies that make use of a masking model, applied to a classic watermarking technique. The joint use of classic frameworks and masking models seems to be one of the trends for the future of research in watermarking. Several tests on the proposed strategies with the state of the art are also offered to give an idea of how to assess the effectiveness of a watermarking technique.

scholarly journals Towards Explanatory Interactive Image Captioning Using Top-Down and Bottom-Up Features, Beam Search and Re-ranking

2020 ◽  
Vol 34 (4) ◽  
pp. 571-584
Author(s):  
Rajarshi Biswas ◽  
Michael Barz ◽  
Daniel Sonntag
Keyword(s):  
State Of The Art ◽  
Input Image ◽  
The State ◽  
Beam Search ◽  
Image Captioning ◽  
Bottom Up ◽  
Interactive Machine Learning ◽  
Joint Embedding ◽  
Bounding Boxes ◽  
High Level

AbstractImage captioning is a challenging multimodal task. Significant improvements could be obtained by deep learning. Yet, captions generated by humans are still considered better, which makes it an interesting application for interactive machine learning and explainable artificial intelligence methods. In this work, we aim at improving the performance and explainability of the state-of-the-art method Show, Attend and Tell by augmenting their attention mechanism using additional bottom-up features. We compute visual attention on the joint embedding space formed by the union of high-level features and the low-level features obtained from the object specific salient regions of the input image. We embed the content of bounding boxes from a pre-trained Mask R-CNN model. This delivers state-of-the-art performance, while it provides explanatory features. Further, we discuss how interactive model improvement can be realized through re-ranking caption candidates using beam search decoders and explanatory features. We show that interactive re-ranking of beam search candidates has the potential to outperform the state-of-the-art in image captioning.

scholarly journals Backbone Cannot Be Trained at Once: Rolling Back to Pre-Trained Network for Person Re-Identification

2019 ◽  
Vol 33 ◽  
pp. 8859-8867 ◽  
Author(s):  
Youngmin Ro ◽  
Jongwon Choi ◽  
Dae Ung Jo ◽  
Byeongho Heo ◽  
Jongin Lim ◽  
...  
Keyword(s):  
Network Architecture ◽  
State Of The Art ◽  
Fine Tuning ◽  
Neural Network Architecture ◽  
Large Dataset ◽  
Low Level ◽  
Tuning Method ◽  
Improved Performance ◽  
High Level ◽  
Tuning Strategy

In person re-identification (ReID) task, because of its shortage of trainable dataset, it is common to utilize fine-tuning method using a classification network pre-trained on a large dataset. However, it is relatively difficult to sufficiently finetune the low-level layers of the network due to the gradient vanishing problem. In this work, we propose a novel fine-tuning strategy that allows low-level layers to be sufficiently trained by rolling back the weights of high-level layers to their initial pre-trained weights. Our strategy alleviates the problem of gradient vanishing in low-level layers and robustly trains the low-level layers to fit the ReID dataset, thereby increasing the performance of ReID tasks. The improved performance of the proposed strategy is validated via several experiments. Furthermore, without any addons such as pose estimation or segmentation, our strategy exhibits state-of-the-art performance using only vanilla deep convolutional neural network architecture.

scholarly journals Empowerment of Women in Fisheries: Evidence from Ganjam District of Odisha

2020 ◽  
pp. 61-68
Author(s):  
Priyanka Patra ◽  
S. S. Dana ◽  
S. B. Ramya Lakshmi
Keyword(s):  
The State ◽  
Composite Score ◽  
Women Empowerment ◽  
Low Level ◽  
Inland Fisheries ◽  
Medium Level ◽  
Good Concentration ◽  
Different Dimensions ◽  
High Level ◽  
Ganjam District

The present study was conducted to assess the empowerment level of women in the fisheries sector in the Ganjam district of Odisha. In the inland sector, the highest numbers of women are of the fishermen population in Ganjam district i.e. 29476 out of a total 263514 number of female fisheries population of the state (Directorate of Fisheries, Government of Odisha, 2015). A very good concentration of women is involving in fisheries activities in this district. But when sector-specific cases are concerned, there are very few studies found where different dimensions of women empowerment through fisheries are discussed. The results revealed that the majority of the respondents (66.60%) in the Inland sector are grouped under a medium level of empowerment followed by low and high-level empowerment (16.70%). These results indicated that there is a significant move towards the empowerment of women in the case of inland fisheries. However, in the Marine sector equal percentage of respondents belonged to both medium and high levels of women empowerment i.e. each 30 (50.00%) and low level of empowerment was nil which indicates the level of empowerment in the marine fisheries activities compared to inland fisheries. With this background, the overall empowerment score was categorized into the low, medium, and high level of empowerment where a majority of the respondents (71.6%) were under the medium level of empowerment followed by the equal percentage of the low and high level of empowerment (14.2%). The composite score of empowerment of women is also encouraging. However, efforts are needed to bring women empowerment from medium level to a higher level. There is also a need to uplift a section of women who are still in the lower category of empowerment.

scholarly journals Ways to improve administrative and legal mechanism for ensuring the rights of business entities in the field of taxation

2020 ◽  
Vol 77 (2) ◽  
pp. 46-80
Author(s):  
А. М. Чорна
Keyword(s):  
Legal Regulation ◽  
The State ◽  
Public Authorities ◽  
The Public ◽  
Low Level ◽  
State Tax ◽  
Business Entities ◽  
High Level ◽  
Legal Mechanism ◽  
Constructive Interaction

The author of the article, based on the analysis of scientific views of scholars and current legislation of Ukraine, elaborates the ways to improve administrative and legal mechanism for ensuring the rights of business entities in the field of taxation. It is substantiated that the objective prerequisites for improving administrative and legal mechanism for ensuring the rights of business entities in the field of taxation are: 1) low level of trust of entrepreneurs in the tax service; 2) high level of corruption in the agencies of the State Tax Service; 3) imperfect mechanism of legal regulation of tax advice; 4) low level of quality and efficiency of functioning of administrative and legal mechanism of ensuring the rights and lawful interests of business entities as taxpayers, etc. It was stated that the first step towards improving administrative and legal mechanism for ensuring the rights of business entities in the field of taxation should be the improvement of the relevant administrative legislation. The expediency of improving the organizational structure of the State Tax Service is substantiated. Emphasis was placed on the need to improve the interaction of the State Tax Service with other public authorities and the public on ensuring the rights of business entities in the field of taxation. It is noted that the deep and constructive interaction of the State Tax Service of Ukraine with other public authorities and the public is undoubtedly an important guarantee of high quality and efficiency for ensuring the rights of business entities.

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