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IEEE International Symposium on Virtual and Intelligent Measurement Systems

作者： Petriu, DC Yang, XL Whalen, TE Carleton Univ Ottawa ON K1S 5B6 Canada

This paper reports development aspects of a behavior-based script language for the animation of anthropomorphic avatars in virtual reality environments.

ISBN: (纸本)0780373448

This paper reports development aspects of a behavior-based script language for the animation of anthropomorphic avatars in virtual reality environments.

关键词： anthropomorphic avatar animation script language virtual reality behavior-based control

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SIMULATED EXPERIENCE EVALUATION IN DEVELOPING MULTI-AGENT COORDINATION GRAPHS

SIMULATED EXPERIENCE EVALUATION IN DEVELOPING MULTI-AGENT CO...

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作者： Andrew G. Watson Air Force Institute of Technology Air University Air Education and Training Command

学位级别：硕士

Cognitive science has proposed that a way people learn is through self-critiquing by generating 'what-if' strategies for events (simulation). It is theorized that people use this method to learn something new as well as to learn more quickly. This research adds this concept to a graph-based genetic program. Memories are recorded during fitness assessment and retained in a global memory bank based on the magnitude of change in the agent's energy and age of the memory. Between generations, candidate agents perform in simulations of the stored memories. Candidates that perform similarly to good memories and differently from bad memories are more likely to be included in the next generation. The simulation- informed genetic program is evaluated in two domains: sequence matching and Robocode. Results indicate the algorithm does not perform equally in all environments. In sequence matching, experiential evaluation fails to perform better than the control. However, in Robocode, the experiential evaluation method initially outperforms the control then stagnates and often regresses. This is likely an indication that the algorithm is over-learning a single solution rather than adapting to the environment and that learning through simulation includes a satisficing component.

关键词： genetic programming mutli-agent system experiential simulated evaluation behavior-based control

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A training simulation system with realistic autonomous ship control

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COMPUTATIONAL INTELLIGENCE 2007年第4期23卷 497-516页

作者： Nicolescu, Monica Leigh, Ryan Olenderski, Adam Louis, Sushil Dascalu, Sergiu Miles, Chris Quiroz, Juan Aleson, Ryan Univ Nevada Reno NV 89557 USA Ancient Paths Musement Orlando FL USA

In this article we present a computational approach to developing effective training systems for virtual simulation environments. In particular, we focus on a Naval simulation system, used for training of conning officers. The currently existing training solutions require multiple expert personnel to control each vessel in a training scenario, or are cumbersome to use by a single instructor. The inability of current technology to provide an automated mechanism for competitive realistic boat behaviors thus compromises the goal of flexible, anytime, anywhere training. In this article we propose an approach that reduces the time and effort required for training of conning officers, by integrating novel approaches to autonomous control within a simulation environment. Our solution is to develop intelligent, autonomous controllers that drive the behavior of each boat. To increase the system's efficiency we provide a mechanism for creating such controllers, from the demonstration of a navigation expert, using a simple programming interface. In addition, our approach deals with two significant and related challenges: the realism of behavior exhibited by the automated boats and their real-time response to changes in the environment. In this article, we describe the control architecture we developed that enables the real-time response of boats and the repertoire of realistic behaviors we designed for this application. We also present our approach for facilitating the automatic authoring of training scenarios and we demonstrate the capabilities of our system with experimental results.

关键词： training systems game artificial intelligence autonomous agents behavior-based control simulations

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behavior coordination and its modification on a brachiation-type mobile robot

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ADVANCED ROBOTICS 2000年第5期14卷 397-398页

作者： Hasegawa, Y Ito, Y Fukuda, T Nagoya Univ Dept Microsyst Engn Chikusa Ku Aichi 4648603 Japan Nagoya Univ Ctr Cooperat Res Adv Sci & Technol Chikusa Ku Aichi 4648601 Japan

A novel adaptation method of a robot, which has a hierarchical behavior controller is proposed. This method adjusts the activation level of each behavior controller for the changes in fewer numbers of trials. The effe... 详细信息

关键词： Brachiation robot adaptation behavior-based control activation value real-time tracking

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MULTI-LAYERED HYBRID ARCHITECTURE TO SOLVE COMPLEX TASKS OF AN AUTONOMOUS MOBILE ROBOT

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International Journal on Artificial Intelligence Tools 1994年第3期3卷 375-381页

作者： F. TIECHE C. FACCHINETTI H. HUGLI Institute of Microtechnology University of Neuchâtel Rue de Tivoli 28 CH-2003 Neuchâtel Switzerland

In this paper, we present the implementation of an autonomous mobile robot controller developed according to the principle of a multi-layered hybrid architecture. This architecture is composed of four layers: sensori-motor, behavioral, sequencing, and strategic. The paper describes its general structure and the function of its main elements. It further analyses the development of an example task presenting the advantages of the hybrid architecture.

关键词： Mobile Robotics Multi-layered Architecture behavior-based control

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Automatic Multi-Robot control Design and Optimization Leveraging Multi-Level Modeling: An Exploration Case Study

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IFAC-PapersOnLine 2023年第2期56卷 11462-11469页

作者： Wakana Endo Cyrill Baumann Hajime Asama Alcherio Martinoli Department of Precision Engineering School of Engineering The University of Tokyo Japan Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering École Polytechnique Fédérale de Lausanne (EPFL) Switzerland

In this work, we demonstrate the applicability of a recently proposed automatic synthesis approach for behavioral arbitrators based on Probabilistic Finite State Machines (PFSMs) for a multi-robot scenario. More specifically, a behavior-based controller for a multi-robot exploration scenario is automatically synthesized using a predefined set of basic behaviors and conditions. A key feature of the used synthesis approach is the tailored use of two modeling levels of the scenario, microscopic and submicroscopic, to significantly reduce the computational effort. Furthermore, the modeling is extended by a simplified macroscopic model of the scenario to analytically evaluate the best achievable performance given an ideal controller, taking into account real-world constraints such as limited speed and localization. Taking advantage of the interpretability of the synthesized PFSM-based arbitrators, individualistic and collaborative controllers are analyzed separately to provide insights into the theoretical and experimental effects of collaboration for the considered case study. The obtained results show that the PFSM-based synthesis approach is also suitable for multi-robot scenarios, and in particular that the collaborative solution can compete with a manually designed and fine-tuned solution.

关键词： Multi-Level Modeling Probabilistic Modeling Learning for control Metaheuristic Optimization Multi-Robot Systems behavior-based control

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

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INTERNATIONAL JOURNAL OF control AUTOMATION AND SYSTEMS 2008年第6期6卷 904-914页

作者： Lee, Sanghoon Suh, Il Hong Kwon, Woo Young Hanyang Univ Coll Informat & Commun Seoul 133791 South Korea

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-into-a-goal (PBIG) will be illustrated.

关键词： Action-selection-mechanism behavior-based control reinforcement learning robot learning

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Development of A behavior-based Cooperative Search Strategy for Distributed Autonomous Mobile Robots Using Zigbee Wireless Sensor Network

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ASIAN JOURNAL OF control 2014年第2期16卷 421-430页

作者： Shih, Tzu-Chiang Yeh, Syh-Shiuh Hsu, Pau-Lo Leader Automat Co Ltd Changhua 51547 Taiwan Natl Taipei Univ Technol Dept Mech Engn Taipei 10608 Taiwan Natl Chiao Tung Univ Dept Elect Engn Hsinchu 30080 Taiwan

To achieve efficient and objective search tasks in an unknown environment, a cooperative search strategy for distributed autonomous mobile robots is developed using a behavior-based control framework with individual and group behaviors. The sensing information of each mobile robot activates the individual behaviors to facilitate autonomous search tasks to avoid obstacles. An 802.15.4 ZigBee wireless sensor network then activates the group behaviors that enable cooperative search among the mobile robots. An unknown environment is dynamically divided into several sub-areas according to the locations and sensing data of the autonomous mobile robots. The group behaviors then enable the distributed autonomous mobile robots to scatter and move in the search environment. The developed cooperative search strategy successfully reduces the search time within the test environments by 22.67% (simulation results) and 31.15% (experimental results).

关键词： Cooperative search strategy distributed mobile robots ZigBee behavior-based control wireless sensor network

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A sensor-based robot controller for autonomous exploration of unknown environments

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INTELLIGENT AUTOMATION AND SOFT COMPUTING 2003年第2期9卷 113-120页

作者： Anderson, GT Cheng, G Univ Arkansas Dept Appl Sci Little Rock AR 72204 USA

This paper describes an oscillator-based controller that was implemented on a two-wheeled, differential drive robot. The controller is loosely based on central pattern generator circuits seen in many animals, and was developed to operate in unknown or changing environments. A unique feature is that the controller adjusts its oscillator parameters based on the pattern of sensory feedback. The controller's performance is evaluated in three different test arenas, each with three variable lighting patterns. The goal of the robot was to seek out areas of bright light and "collect" as much light as possible during a trial. The results indicate that the performance of the self-adjusting oscillator-based controller exceeds that of a fixed-oscillator controller, with the performance difference increasing as the complexity of the environment increases.

关键词： coupled oscillators behavior-based control sensor-based control self-adjusting controller

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Formation Transformation based on Leader-Follower Algorithm

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INTERNATIONAL JOURNAL OF TECHNOLOGY AND HUMAN INTERACTION 2019年第3期15卷 28-46页

作者： Duan, Yanyu Gao, Zhiqiang Peng, Zhensheng Yang, Wenshuai Wang, Yun Engn Univ Peoples Armed Police Xian Shaanxi Peoples R China

A method based on the leader-follower algorithm is proposed for transformation among the formations. The introduction of the greedy algorithm, behavior-based control and virtual structure help realize the region division and the calculation of the distribution of the leaders and followers in target formation. Collision detection and collision avoidance are proposed to solve path conflicts with error free feedback and effectively maintain the stability of motion. The modeling of transformation is simulated by the shape from a line to a wedged, in which the formation is adjusted by the distance difference obtained by feedback. The experimental results show that it is feasible and effective to implement the formation conversion and formation control, and the system possess a better robustness and stability.

关键词： behavior-based control Collision Avoidance And control Follower-Leader Algorithm Formation control Formation Transformation Genetic Algorithm Greedy Algorithm

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