Boosted curriculum reinforcement learning
Curriculum value-based reinforcement learning (RL) solves a complex target task by reusing
action-values across a tailored sequence of related tasks of increasing difficulty. However …
action-values across a tailored sequence of related tasks of increasing difficulty. However …
Learning to learn with active adaptive perception
Increasingly, autonomous agents will be required to operate on long-term missions. This will
create a demand for general intelligence because feedback from a human operator may be …
create a demand for general intelligence because feedback from a human operator may be …
Global versus local constructive function approximation for on-line reinforcement learning
P Vamplew, R Ollington - Australasian Joint Conference on Artificial …, 2005 - Springer
In order to scale to large state-spaces, reinforcement learning (RL) algorithms need to apply
function approximation techniques. Research on function approximation for RL has so far …
function approximation techniques. Research on function approximation for RL has so far …
The Logic of Adaptive Behavior-Knowledge Representation and Algorithms for the Markov Decision Process Framework in First-Order Domains
M Van Otterlo - 2008 - research.utwente.nl
Learning and reasoning in large, structured, probabilistic worlds is at the heart of artificial
intelligence. Markov decision processes have become the de facto standard in modeling …
intelligence. Markov decision processes have become the de facto standard in modeling …
Dynamic network architectures for deep q-learning: Modelling neurogenesis in artificial intelligence
P Eriksson, L Westlund Gotby - 2019 - odr.chalmers.se
Artificial neural networks have become popular within a range of machine learning fields for
their ability to solve complex problems, with one of the uses as function approximators in Q …
their ability to solve complex problems, with one of the uses as function approximators in Q …
[PDF][PDF] Reinforcement learning with limited prior knowledge in long-term environments
D Bossens - 2020 - drive.google.com
It has been estimated that by 2030 global GDP could increase by 13.8% merely due to the
impact of Artificial Intelligence (AI). AI has become an instrumental part of nearly all human …
impact of Artificial Intelligence (AI). AI has become an instrumental part of nearly all human …
Towards the Learning Behaviour and Performance of Artificial Neural Networks in Production Control
B Scholz-Reiter, F Harjes - … LDIC 2012 Bremen, Germany, February/March …, 2013 - Springer
Recently, artificial neural networks have proven their potential in manifold production related
tasks. At this, the learning ability is both their greatest strength and greatest weakness. The …
tasks. At this, the learning ability is both their greatest strength and greatest weakness. The …
Towards the Learning Behaviour
B Scholz-Reiter, F Harjes - Dynamics in Logistics: Third …, 2013 - books.google.com
Recently, artificial neural networks have proven their potential in manifold production related
tasks. At this, the learning ability is both their greatest strength and greatest weakness. The …
tasks. At this, the learning ability is both their greatest strength and greatest weakness. The …
[PDF][PDF] THE LOGIC OF ADAPTIVE BEHAVIOR
ASD MAKING, UIN FIRST-ORDER - 2008 - martijnvanotterlo.nl
One of my favorite stories is The Library of Babel (1941) by the Argentinean writer and
librarian Jorge Luis Borges (1899–1986). In this fantastic story, Borges describes an …
librarian Jorge Luis Borges (1899–1986). In this fantastic story, Borges describes an …