most citedModel-Based Episodic Memory Induces Dynamic Hybrid Controls

3 citations · 7 across the 5 of their papers we have counts for

collaborators

7 papers

cs.LG20213 cited

Model-Based Episodic Memory Induces Dynamic Hybrid Controls

Hung Le, Thommen Karimpanal George, Majid Abdolshah +2

Episodic control enables sample efficiency in reinforcement learning by recalling past experiences from an episodic memory. We propose a new model-based episodic memory of trajecto…

cs.LG20211 cited

Balanced Q-learning: Combining the Influence of Optimistic and Pessimistic Targets

Thommen George Karimpanal, Hung Le, Majid Abdolshah +4

The optimistic nature of the Q-learning target leads to an overestimation bias, which is an inherent problem associated with standard learning. Such a bias fails to account for…

cs.LG2021

Plug and Play, Model-Based Reinforcement Learning

Majid Abdolshah, Hung Le, Thommen Karimpanal George +3

Sample-efficient generalisation of reinforcement learning approaches have always been a challenge, especially, for complex scenes with many components. In this work, we introduce P…

cs.LG20213 cited

A New Representation of Successor Features for Transfer across Dissimilar Environments

Majid Abdolshah, Hung Le, Thommen Karimpanal George +3

Transfer in reinforcement learning is usually achieved through generalisation across tasks. Whilst many studies have investigated transferring knowledge when the reward function ch…

cs.LG2019

Cost-aware Multi-objective Bayesian optimisation

Majid Abdolshah, Alistair Shilton, Santu Rana +2

The notion of expense in Bayesian optimisation generally refers to the uniformly expensive cost of function evaluations over the whole search space. However, in some scenarios, the…

stat.ML2019

Stable Bayesian Optimisation via Direct Stability Quantification

Alistair Shilton, Sunil Gupta, Santu Rana +3

In this paper we consider the problem of finding stable maxima of expensive (to evaluate) functions. We are motivated by the optimisation of physical and industrial processes where…