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» Feudal Reinforcement Learning
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CORR
2010
Springer
152views Education» more  CORR 2010»
13 years 8 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
CI
2005
106views more  CI 2005»
13 years 8 months ago
Incremental Learning of Procedural Planning Knowledge in Challenging Environments
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
Douglas J. Pearson, John E. Laird
ACMICEC
2007
ACM
154views ECommerce» more  ACMICEC 2007»
14 years 10 days ago
Learning and adaptivity in interactive recommender systems
Recommender systems are intelligent E-commerce applications that assist users in a decision-making process by offering personalized product recommendations during an interaction s...
Tariq Mahmood, Francesco Ricci
JAIR
2008
148views more  JAIR 2008»
13 years 8 months ago
Learning Partially Observable Deterministic Action Models
We present exact algorithms for identifying deterministic-actions' effects and preconditions in dynamic partially observable domains. They apply when one does not know the ac...
Eyal Amir, Allen Chang
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
13 years 9 months ago
On the effects of node duplication and connection-oriented constructivism in neural XCSF
For artificial entities to achieve high degrees of autonomy they will need to display appropriate adaptability. In this sense adaptability includes representational flexibility gu...
Gerard David Howard, Larry Bull