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ICML
1994
IEEE
13 years 11 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...
AI
2006
Springer
13 years 11 months ago
Adaptive Fraud Detection Using Benford's Law
Abstract. Adaptive Benford's Law [1] is a digital analysis technique that specifies the probabilistic distribution of digits for many commonly occurring phenomena, even for in...
Fletcher Lu, J. Efrim Boritz, H. Dominic Covvey
ICCS
1993
Springer
13 years 11 months ago
Towards Domain-Independent Machine Intelligence
Adaptive predictive search (APS), is a learning system framework, which given little initial domain knowledge, increases its decision-making abilities in complex problems domains....
Robert Levinson
ENTER
2008
Springer
13 years 9 months ago
Adaptive Recommender Systems for Travel Planning
Conversational recommender systems have been introduced in Travel and Tourism applications in order to support interactive dialogues which assist users in acquiring their goals, e...
Tariq Mahmood, Francesco Ricci, Adriano Venturini,...
AAMAS
2005
Springer
13 years 7 months ago
Cooperative Multi-Agent Learning: The State of the Art
Cooperative multi-agent systems are ones in which several agents attempt, through their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among t...
Liviu Panait, Sean Luke