143 citations · 1.1k across the 106 of their papers we have counts for
6 papers · 1 filter
Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning
Dung Nguyen, Svetha Venkatesh, Phuoc Nguyen +1
Guilt aversion induces experience of a utility loss in people if they believe they have disappointed others, and this promotes cooperative behaviour in human. In psychological game…
Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning
Thommen George Karimpanal, Santu Rana, Sunil Gupta +2
Prior access to domain knowledge could significantly improve the performance of a reinforcement learning agent. In particular, it could help agents avoid potentially catastrophic e…
Relational dynamic memory networks
Trang Pham, Truyen Tran, Svetha Venkatesh
Neural networks excel in detecting regular patterns but are less successful in representing and manipulating complex data structures, possibly due to the lack of an external memory…
Knowledge Graph Embedding with Multiple Relation Projections
Kien Do, Truyen Tran, Svetha Venkatesh
Knowledge graphs contain rich relational structures of the world, and thus complement data-driven machine learning in heterogeneous data. One of the most effective methods in repre…
Tree-based iterated local search for Markov random fields with applications in image analysis
Truyen Tran, Dinh Phung, Svetha Venkatesh
The \emph{maximum a posteriori} (MAP) assignment for general structure Markov random fields (MRFs) is computationally intractable. In this paper, we exploit tree-based methods to e…
Policy Recognition in the Abstract Hidden Markov Model
H. H. Bui, S. Venkatesh, G. West
In this paper, we present a method for recognising an agent's behaviour in dynamic, noisy, uncertain domains, and across multiple levels of abstraction. We term this problem on-lin…