2 citations · 3 across the 5 of their papers we have counts for
5 papers
Strategy Extraction in Single-Agent Games
Archana Vadakattu, Michelle Blom, Adrian R. Pearce
The ability to continuously learn and adapt to new situations is one where humans are far superior compared to AI agents. We propose an approach to knowledge transfer using behavio…
Sampling from Pre-Images to Learn Heuristic Functions for Classical Planning
Stefan O'Toole, Miquel Ramirez, Nir Lipovetzky +1
We introduce a new algorithm, Regression based Supervised Learning (RSL), for learning per instance Neural Network (NN) defined heuristic functions for classical planning problems.…
Efficient Multi-agent Epistemic Planning: Teaching Planners About Nested Belief
Christian Muise, Vaishak Belle, Paolo Felli +4
Many AI applications involve the interaction of multiple autonomous agents, requiring those agents to reason about their own beliefs, as well as those of other agents. However, pla…
Width-based Lookaheads with Learnt Base Policies and Heuristics Over the Atari-2600 Benchmark
Stefan O'Toole, Nir Lipovetzky, Miquel Ramirez +1
We propose new width-based planning and learning algorithms inspired from a careful analysis of the design decisions made by previous width-based planners. The algorithms are appli…
Social planning for social HRI
Liz Sonenberg, Tim Miller, Adrian Pearce +3
Making a computational agent 'social' has implications for how it perceives itself and the environment in which it is situated, including the ability to recognise the behaviours of…