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117
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ICML
1994
IEEE
15 years 4 months ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
115
Voted
LION
2007
Springer
192views Optimization» more  LION 2007»
15 years 6 months ago
Learning While Optimizing an Unknown Fitness Surface
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Roberto Battiti, Mauro Brunato, Paolo Campigotto
121
Voted
HT
2009
ACM
15 years 7 months ago
Improving recommender systems with adaptive conversational strategies
Conversational recommender systems (CRSs) assist online users in their information-seeking and decision making tasks by supporting an interactive process. Although these processes...
Tariq Mahmood, Francesco Ricci
77
Voted
ATAL
2007
Springer
15 years 6 months ago
Dynamic task allocation within an open service-oriented MAS architecture
A MAS architecture consisting of service centers is proposed. Within each service center, a mediator coordinates service delivery by allocating individual tasks to corresponding t...
Ivan Jureta, Stéphane Faulkner, Youssef Ach...
112
Voted
GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
15 years 4 months ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson