Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms
International Journal of Man-Machine Studies - Special issue: symbolic problem solving in noisy and novel task environments
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Neuro-Dynamic Programming
Learning to Predict by the Methods of Temporal Differences
Machine Learning
Practical Reinforcement Learning in Continuous Spaces
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Karlsruhe Brainstormers - A Reinforcement Learning Approach to Robotic Soccer
RoboCup 2001: Robot Soccer World Cup V
RoboCup-99: Robot Soccer World Cup III
Qualitative Velocity and Ball Interception
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
A hybrid genetic algorithm for classification
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Using evolution programs to learn local similarity measures
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
An Analysis of Case-Based Value Function Approximation by Approximating State Transition Graphs
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Instance-Based Action Models for Fast Action Planning
RoboCup 2007: Robot Soccer World Cup XI
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Improving Reinforcement Learning by Using Case Based Heuristics
ICCBR '09 Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Transfer learning in real-time strategy games using hybrid CBR/RL
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Case-Based Multiagent Reinforcement Learning: Cases as Heuristics for Selection of Actions
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Multi-agent case-based reasoning for cooperative reinforcement learners
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
Using cases as heuristics in reinforcement learning: a transfer learning application
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
On-Line model-based continuous state reinforcement learning using background knowledge
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Safe exploration of state and action spaces in reinforcement learning
Journal of Artificial Intelligence Research
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CBR is one of the techniques that can be applied to the task of approximating a function over high-dimensional, continuous spaces. In Reinforcement Learning systems a learning agent is faced with the problem of assessing the desirability of the state it finds itself in. If the state space is very large and/or continuous the availability of a suitable mechanism to approximate a value function – which estimates the value of single states – is of crucial importance. In this paper, we investigate the use of case-based methods to realise that task. The approach we take is evaluated in a case study in robotic soccer simulation.