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A Formal Analysis and Taxonomy of Task Allocation in Multi-Robot Systems
A domain-independent taxonomy of MRTA problems is given, and it is shown how many such problems can be viewed as instances of other, well-studied, optimization problems. Expand
Mobile Sensor Network Deployment using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem
This paper presents a potential-field-based approach to deployment of a mobile sensor network, where the fields are constructed such that each node is repelled by both obstacles and by other nodes, thereby forcing the network to spread itself throughout the environment. Expand
Sold!: auction methods for multirobot coordination
The primary contribution of the paper is to show empirically that distributed negotiation mechanisms such as MURDOCH are viable and effective for coordinating physical multirobot systems. Expand
Toward the Evolution of Dynamical Neural Networks for Minimally Cognitive Behavior
The results of preliminary experiments on the evolution of dynamical neural networks for visually-guided orientation, object discrimination and accurate pointing with a simple manipulator to objects appearing in its field of view are presented. Expand
Defining socially assistive robotics
This paper defines the research area of socially assistive robotics, focusing on assisting people through social interaction. While much attention has been paid to robots that provide assistance toExpand
Robots for use in autism research.
The past decade's work in SAR systems designed for autism therapy is discussed by analyzing robot design decisions, human-robot interactions, and system evaluations and discusses challenges and future trends for this young but rapidly developing research area. Expand
Interaction and intelligent behavior
A novel formulation of reinforcement learning is proposed that makes behavior selection learnable in noisy, uncertain multi-agent environments with stochastic dynamics, and enables and accelerates learning in complex multi-robot domains. Expand
Natural methods for robot task learning: instructive demonstrations, generalization and practice
An approach for teaching robots that relies on the key features and the general approach people use when teaching each other: first give a demonstration, then allow the learner to refine the acquired capabilities by practicing under the teacher's supervision, involving a small number of trials. Expand
Reward Functions for Accelerated Learning
A methodology for designing reinforcement functions that take advantage of implicit domain knowledge in order to accelerate learning in situated domains characterized by multiple goals, noisy state, and inconsistent reinforcement is proposed. Expand
Automated Derivation of Primitives for Movement Classification
A method for automatically deriving a set of primitives directly from human movement data, using movement data gathered from a psychophysical experiment on human imitation to derive the primitives. Expand