The Experts below are selected from a list of 4791 Experts worldwide ranked by ideXlab platform
Marcos S. G. Tsuzuki - One of the best experts on this subject based on the ideXlab platform.
-
Swarm Intelligence applied in synthesis of hunting strategies in a Three-Dimensional Environment
Expert Systems with Applications, 2008Co-Authors: E. G. Castro, Marcos S. G. TsuzukiAbstract:Systems of distributed artificial intelligence can be powerful tools in a wide variety of practical applications. Its most surprising characteristic, the emergent behavior, is also the most answerable for the difficulty in projecting these systems. This work proposes a tool capable to beget individual strategies for the elements of a multi-agent system and thereof providing to the group means on obtaining wanted results, working in a coordinated and cooperative manner as well. As an application example, a problem was taken as a basis where a predators' group must catch a prey in a Three-Dimensional continuous ambient. A synthesis of system strategies was implemented of which internal mechanism involves the integration between simulators by Particle Swarm Optimization algorithm (PSO), a Swarm Intelligence technique. The system had been tested in several simulation settings and it was capable to synthesize automatically successful hunting strategies, substantiating that the developed tool can provide, as long as it works with well-elaborated patterns, satisfactory solutions for problems of complex nature, of difficult resolution starting from analytical approaches. © 2007 Elsevier Ltd. All rights reserved.
E. G. Castro - One of the best experts on this subject based on the ideXlab platform.
-
Swarm Intelligence applied in synthesis of hunting strategies in a Three-Dimensional Environment
Expert Systems With Applications, 2008Co-Authors: E. G. Castro, Marcos De Sales Guerra TsuzukiAbstract:Systems of distributed artificial intelligence can be powerful tools in a wide variety of practical applications. Its most surprising characteristic, the emergent behavior, is also the most answerable for the difficulty in projecting these systems. This work proposes a tool capable to beget individual strategies for the elements of a multi-agent system and thereof providing to the group means on obtaining wanted results, working in a coordinated and cooperative manner as well. As an application example, a problem was taken as a basis where a predators' group must catch a prey in a Three-Dimensional continuous ambient. A synthesis of system strategies was implemented of which internal mechanism involves the integration between simulators by Particle Swarm Optimization algorithm (PSO), a Swarm Intelligence technique. The system had been tested in several simulation settings and it was capable to synthesize automatically successful hunting strategies, substantiating that the developed tool can provide, as long as it works with well-elaborated patterns, satisfactory solutions for problems of complex nature, of difficult resolution starting from analytical approaches.
-
Swarm Intelligence applied in synthesis of hunting strategies in a Three-Dimensional Environment
Expert Systems with Applications, 2008Co-Authors: E. G. Castro, Marcos S. G. TsuzukiAbstract:Systems of distributed artificial intelligence can be powerful tools in a wide variety of practical applications. Its most surprising characteristic, the emergent behavior, is also the most answerable for the difficulty in projecting these systems. This work proposes a tool capable to beget individual strategies for the elements of a multi-agent system and thereof providing to the group means on obtaining wanted results, working in a coordinated and cooperative manner as well. As an application example, a problem was taken as a basis where a predators' group must catch a prey in a Three-Dimensional continuous ambient. A synthesis of system strategies was implemented of which internal mechanism involves the integration between simulators by Particle Swarm Optimization algorithm (PSO), a Swarm Intelligence technique. The system had been tested in several simulation settings and it was capable to synthesize automatically successful hunting strategies, substantiating that the developed tool can provide, as long as it works with well-elaborated patterns, satisfactory solutions for problems of complex nature, of difficult resolution starting from analytical approaches. © 2007 Elsevier Ltd. All rights reserved.
V.j. Lumelsky - One of the best experts on this subject based on the ideXlab platform.
-
Motion planning for three-link robot arm manipulators operating in an unknown Three-Dimensional Environment
[1991] Proceedings of the 30th IEEE Conference on Decision and Control, 1991Co-Authors: V.j. LumelskyAbstract:The authors present a general motion planning strategy for a class of three-link robot arm manipulators operating in an unknown 2D or 3D Environment. Each joint of the robot arm manipulator can be either revolute or sliding. Out of eight possible combinations of kinematic linkages, the approach presented applies to those four combinations for which the third joint is sliding; this covers a variety of arm manipulators used in practice. It is shown that the free configuration space of such a robot arm has a 2D deformation retract which allows the reduction of the dimensionality of the motion planning problem. Then, existing 2D motion planning strategies can be appropriately modified to produce algorithms for planning collision-free motion for the whole body of the robot arm in a 3D Environment with unknown obstacles of arbitrary shape.
Leonard Barolli - One of the best experts on this subject based on the ideXlab platform.
-
EIDWT - A DQN Based Mobile Actor Node Control in WSAN: Simulation Results of Different Distributions of Events Considering Three-Dimensional Environment
Advances in Internet Data and Web Technologies, 2020Co-Authors: Kyohei Toyoshima, Masaharu Hirota, Kengo Katayama, Leonard BarolliAbstract:Wireless Sensor Actor Networks (WSANs) consist of wireless network nodes, with the ability to sense events (sensors) and to perform actuations (actors) based on the sensing data collected by all sensors. This paper describes a design of a simulation system based on Deep Q-Network (DQN) for actor node mobility control in WSANs. DQN is a deep neural network structure used for estimation of Q value of the Q-learning technique. The proposed simulation system is implemented in Rust programming language. We evaluate the performance of the proposed system for different distributions of event placement considering Three-Dimensional Environment. For this scenario, the simulation results show that for normal distribution of events actor nodes are connected in the best case.
-
CISIS - A Deep Q-Network Based Simulation System for Actor Node Mobility Control in WSANs Considering Three-Dimensional Environment: A Comparison Study for Normal and Uniform Distributions
Advances in Intelligent Systems and Computing, 2018Co-Authors: Elis Kulla, Kengo Katayama, Makoto Ikeda, Leonard BarolliAbstract:A Wireless Sensor and Actor Network (WSAN) is a group of wireless devices with the ability to sense physical events (sensors) or/and to perform relatively complicated actions (actors), based on the sensed data shared by sensors. This paper presents design and implementation of a simulation system based on Deep Q-Network (DQN) for actor node mobility control in WSANs. DQN is a deep neural network structure used for estimation of Q-value of the Q-learning method. We implemented the proposed simulating system by Rust programming language. We evaluated the performance of proposed system for normal and uniform distributions of events considering Three-Dimensional Environment. For this scenario, the simulation results show that for normal distribution of events and the best episode all actor nodes are connected.
-
INCoS - Performance Evaluation of a Deep Q-Network Based Simulation System for Actor Node Mobility Control in Wireless Sensor and Actor Networks Considering Three-Dimensional Environment
Advances in Intelligent Networking and Collaborative Systems, 2017Co-Authors: Donald Elmazi, Miralda Cuka, Elis Kulla, Makoto Ikeda, Leonard BarolliAbstract:A Wireless Sensor and Actor Network (WSAN) is a group of wireless devices with the ability to sense physical events (sensors) or/and to perform relatively complicated actions (actors), based on the sensed data shared by sensors. This paper presents design and implementation of a simulation system based on Deep Q-Network (DQN) for actor node mobility control in WSANs. DQN is a deep neural network structure used for estimation of Q-value of the Q-learning method. We implemented the proposed simulating system by Rust programming language. We evaluated the performance of proposed system for normal distribution of events considering Three-Dimensional Environment. For this scenario, the simulation results show that for normal distribution of events and the best episode all actor nodes are connected but one event is not covered.
Yu Zhou - One of the best experts on this subject based on the ideXlab platform.
-
A coverage strategy for wireless sensor networks in a three–dimensional Environment
International Journal of Ad Hoc and Ubiquitous Computing, 2014Co-Authors: Lin Feng, Yu ZhouAbstract:Coverage is one of the fundamental issues in wireless sensor networks (WSNs). The detection area is non–ideal and the terrain of the detection area is more complex in applications of three–dimensional sensor networks. Consequently, many of the existing coverage strategies cannot be directly applied to three–dimensional spaces. This paper presents a new coverage strategy for the three–dimensional sensor networks. Sensor nodes are uniformly distributed. The cost factor is utilised to construct the perceived probability and the classical watershed algorithm after the transformation of points from the three–dimensional space to the two–dimensional plane using the dimensionality reduction method, which can maintain the topology characteristic of the non–linear terrain. The detection probability in the optimal breath path is used as the measure to evaluate the coverage. Simulation results indicate that the proposed strategy can determine the coverage with fewer nodes, while achieving the coverage requirements of the networks.
-
A Coverage Strategy for Wireless Sensor Networks in a Three-Dimensional Environment
arXiv: Networking and Internet Architecture, 2013Co-Authors: Lin Feng, Yu ZhouAbstract:Coverage is one of the fundamental issues in wireless sensor networks (WSNs). It reflects the ability of WSNs to detect the fields of interest. In a real sensor networks application, the detection area is always non-ideal and the terrain of the detection area is often more complex in applications of Three-Dimensional sensor networks. Consequently, many of the existing coverage strategies cannot be directly applied to Three-Dimensional spaces. This paper presents a new coverage strategy for the Three-Dimensional sensor networks. Sensor nodes are uniformly distributed. The cost factor is utilized to construct the perceived probability and the classical watershed algorithm after the transformation of points from the Three-Dimensional space to the two-dimensional plane using the dimensionality reduction method, which can maintain the topology characteristic of the non-linear terrain. The detection probability in the optimal breath path is used as the measure to evaluate the coverage. Simulation results indicate that the proposed strategy can determine the coverage with fewer nodes, while achieving the coverage requirements of the networks.