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ACL
2009
13 years 6 months ago
Reinforcement Learning for Mapping Instructions to Actions
In this paper, we present a reinforcement learning approach for mapping natural language instructions to sequences of executable actions. We assume access to a reward function tha...
S. R. K. Branavan, Harr Chen, Luke S. Zettlemoyer,...
CLIMA
2007
13 years 9 months ago
Actions with Failures in Interval Temporal Logic
Abstract. Failures are unavoidable in many circumstances. For example, an agent may fail at some point to perform a task in a dynamic environment. Robust systems typically have mec...
Arjen Hommersom, Peter J. F. Lucas
IJCNN
2006
IEEE
14 years 2 months ago
Language Acquisition and Symbol Grounding Transfer with Neural Networks and Cognitive Robots
— Neural networks have been proposed as an ideal cognitive modeling methodology to deal with the symbol grounding problem. More recently, such neural network approaches have been...
Angelo Cangelosi, Emmanouil Hourdakis, Vadim Tikha...
ATAL
2005
Springer
14 years 1 months ago
Using the UML 2.0 activity diagram to model agent plans and actions
The behavior of an agent is defined through the specification of plans and actions. Agents have a set of plans that are selected to be executed according to their goals (and other...
Viviane Torres da Silva, Ricardo Choren, Carlos Jo...
AAAI
2006
13 years 9 months ago
Learning Partially Observable Action Schemas
We present an algorithm that derives actions' effects and preconditions in partially observable, relational domains. Our algorithm has two unique features: an expressive rela...
Dafna Shahaf, Eyal Amir