A Markov analysis of social learning and adaptation

[Adaptation, Learning, and Optimization]

[Adaptation, Learning, and Optimization] Reinforcement Learning Volume 12 || Reinforcement Learning and Markov Decision Processes

✍ Wiering, Marco; van Otterlo, Martijn 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg 🌐 German ⚖ 660 KB

Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement l

[Adaptation, Learning, and Optimization]

[Adaptation, Learning, and Optimization] Reinforcement Learning Volume 12 || Partially Observable Markov Decision Processes

✍ Wiering, Marco; van Otterlo, Martijn 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg 🌐 German ⚖ 624 KB

Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement l

A reinforcement learning neural network

A reinforcement learning neural network for adaptive control of Markov chains

✍ Santharam, G.; Sastry, P.S. 📂 Article 📅 1997 🏛 IEEE 🌐 English ⚖ 570 KB

[Adaptation, Learning, and Optimization]

[Adaptation, Learning, and Optimization] Markov Networks in Evolutionary Computation Volume 14 || A Review of Estimation of Distribution Algorithms and Markov Networks

✍ Shakya, Siddhartha; Santana, Roberto 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg 🌐 English ⚖ 501 KB

Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs). EDAs have arisen as one of the most successful experiences in the application of

[Adaptation, Learning, and Optimization]

[Adaptation, Learning, and Optimization] Markov Networks in Evolutionary Computation Volume 14 || Probabilistic Graphical Models and Markov Networks

✍ Shakya, Siddhartha; Santana, Roberto 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg 🌐 English ⚖ 395 KB

Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs). EDAs have arisen as one of the most successful experiences in the application of

Online Learning and Acoustic Feature Ada

Online Learning and Acoustic Feature Adaptation in Large-Margin Hidden Markov Models

✍ Chih-Chieh Cheng; Fei Sha; Saul, L.K. 📂 Article 📅 2010 🏛 Institute of Electrical and Electronics Engineers 🌐 English ⚖ 922 KB