No two wolves are the same. Some of the variations between individuals such as variation in mass and age have major implications on their hunting abilities. The predatory success of a wolf pack has been found to depen...
No two wolves are the same. Some of the variations between individuals such as variation in mass and age have major implications on their hunting abilities. The predatory success of a wolf pack has been found to depen...
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No two wolves are the same. Some of the variations between individuals such as variation in mass and age have major implications on their hunting abilities. The predatory success of a wolf pack has been found to depend on its composition of individuals along these dimensions. Building from a system for simulating wolf hunting behavior in earlier work [1], this paper explores the effects of heterogeneity among individuals in a team and the utility of these variations for the team as a whole. The implications for robot team control and organization are presented.
The design and implementation of mood as an affective component for robotic behavior is described in the context of the TAME framework - a comprehensive, time-varying affective model for robotic behavior that encompas...
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The design and implementation of mood as an affective component for robotic behavior is described in the context of the TAME framework - a comprehensive, time-varying affective model for robotic behavior that encompas...
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The design and implementation of mood as an affective component for robotic behavior is described in the context of the TAME framework - a comprehensive, time-varying affective model for robotic behavior that encompasses personality traits, attitudes, moods, and emotions. Furthermore, a method for continuously adapting TAME's Mood component (and thereby the overall affective system) to individual preference is explored by applying Learning Momentum, which is a parametric adjustment learning algorithm that has been successfully applied in the past to improve navigation performance in real-time, reactive robotic systems.
Wolves are one of the most successful large predators on earth. Their success is made apparent by their presence in most northern ecosystems. They owe much of this success to their generalized hunting behavior which a...
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ISBN:
(纸本)9781424493197
Wolves are one of the most successful large predators on earth. Their success is made apparent by their presence in most northern ecosystems. They owe much of this success to their generalized hunting behavior which allows them to quickly and effectively adjust to different species of prey. The success of this hunting behavior for wolves is the inspiration for a project to bestow this behavior onto a system of robots with the hopes that they might utilize the apparent strengths of the behavior to achieve their own success.
Wolves are one of the most successful large predators on earth. Their success is made apparent by their presence in most northern ecosystems. They owe much of this success to their generalized hunting behavior which a...
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This paper explores methods and representations that allow two perceptually heterogeneous robots, each of which represents concepts via grounded properties, to transfer knowledge despite their differences. This is an ...
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This paper explores methods and representations that allow two perceptually heterogeneous robots, each of which represents concepts via grounded properties, to transfer knowledge despite their differences. This is an important issue, as it will be increasingly important for robots to communicate and effectively share knowledge to speed up learning as they become more ubiquitous. We use Ga¿rdenfors' conceptual spaces to represent objects as a fuzzy combination of properties such as color and texture, where properties themselves are represented as Gaussian Mixture Models in a metric space. We then use confusion matrices that are built using instances from each robot, obtained in a shared context, in order to learn mappings between the properties of each robot. These mappings are then used to transfer a concept from one robot to another, where the receiving robot was not previously trained on instances of the objects. We show in a 3D simulation environment that these models can be successfully learned and concepts can be transferred between a ground robot and an aerial quadrotor robot.
This paper presents the motivation, basis and a prototype implementation of an ethical adaptor capable of using a moral affective function, guilt, as a basis for altering a robot's ongoing behavior. While the rese...
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ISBN:
(纸本)9781424448081
This paper presents the motivation, basis and a prototype implementation of an ethical adaptor capable of using a moral affective function, guilt, as a basis for altering a robot's ongoing behavior. While the research is illustrated in the context of the battlefield, the methods described are believed generalizable to other domains such as eldercare and are potentially extensible to a broader class of moral emotions, including compassion and empathy.
Lek behavior is a biological mechanism used by male birds to attract mates by forming a group. This project explores the use of a biological behavior found in many species of birds to form leks to guide the creation o...
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ISBN:
(纸本)9781424447749
Lek behavior is a biological mechanism used by male birds to attract mates by forming a group. This project explores the use of a biological behavior found in many species of birds to form leks to guide the creation of groups of robots. The lek behavior provides a sound basis for multi-robot formation because it demonstrates a group of individual entities forming up around a scarce resource. This behavior can be useful to robots in many situations, with an example scenario the case in which robots were dropped via parachute into an area and then needed to form meaningful task-oriented groups.
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