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» Learning Policies for Embodied Virtual Agents through Demons...
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SIGECOM
2009
ACM
114views ECommerce» more  SIGECOM 2009»
13 years 11 months ago
Policy teaching through reward function learning
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...
Haoqi Zhang, David C. Parkes, Yiling Chen
ATAL
2008
Springer
13 years 6 months ago
Teaching multi-robot coordination using demonstration of communication and state sharing
Solutions to complex tasks often require the cooperation of multiple robots, however, developing multi-robot policies can present many challenges. In this work, we introduce teach...
Sonia Chernova, Manuela M. Veloso
ROMAN
2007
IEEE
220views Robotics» more  ROMAN 2007»
13 years 10 months ago
Embodiment and Human-Robot Interaction: A Task-Based Perspective
— In this work, we further test the hypothesis that physical embodiment has a measurable effect on performance and impression of social interactions. Support for this hypothesis ...
Joshua Wainer, David Feil-Seifer, Dylan A. Shell, ...
AAAI
2010
13 years 5 months ago
Bayesian Policy Search for Multi-Agent Role Discovery
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
Aaron Wilson, Alan Fern, Prasad Tadepalli
ATAL
2009
Springer
13 years 11 months ago
A self-organizing neural network architecture for intentional planning agents
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic ...
Budhitama Subagdja, Ah-Hwee Tan