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» Planning Partially for Situated Agents
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ATAL
2009
Springer
14 years 2 months ago
An empirical analysis of value function-based and policy search reinforcement learning
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
Shivaram Kalyanakrishnan, Peter Stone
AAAI
2004
13 years 9 months ago
Mixed-Initiative Workflow Composition
CAT's knowledge base contains abstract task or example "abstract flight reservation task," which can be included in a workflow as placeholders. CAT will gest that us...
Marc Spraragen
EUROCAST
2007
Springer
182views Hardware» more  EUROCAST 2007»
14 years 2 months ago
A k-NN Based Perception Scheme for Reinforcement Learning
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
José Antonio Martin H., Javier de Lope Asia...
NECO
2007
150views more  NECO 2007»
13 years 7 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
RTAS
2005
IEEE
14 years 1 months ago
Convoy Driving through Ad-Hoc Coalition Formation
— Convoy driving on public highways is a useful phenomena which increases the safety and the throughput of the highway. We present an approach through which a wireless Convoy Dri...
Majid Ali Khan, Ladislau Bölöni