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of 251
pro vyhledávání: '"Pearce, Adrian"'
We present a Large Neighbourhood Search (LNS) based approach for solving complex long-term open-pit mine planning problems. An initial feasible solution, generated by a sliding windows heuristic, is improved through repeated solves of a restricted mi
Externí odkaz:
http://arxiv.org/abs/2403.18213
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 behavioural strategies as a form of transferable knowledge influenced by the
Externí odkaz:
http://arxiv.org/abs/2305.12623
We introduce a new algorithm, Regression based Supervised Learning (RSL), for learning per instance Neural Network (NN) defined heuristic functions for classical planning problems. RSL uses regression to select relevant sets of states at a range of d
Externí odkaz:
http://arxiv.org/abs/2207.03336
Autor:
Muise, Christian, Belle, Vaishak, Felli, Paolo, McIlraith, Sheila, Miller, Tim, Pearce, Adrian R., Sonenberg, Liz
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, planning involving nested beliefs is known to be computationally challeng
Externí odkaz:
http://arxiv.org/abs/2110.02480
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 applied over the Atari-2600 games and our best performing algorithm, Novelt
Externí odkaz:
http://arxiv.org/abs/2106.12151
Autor:
Muise, Christian, Belle, Vaishak, Felli, Paolo, McIlraith, Sheila, Miller, Tim, Pearce, Adrian R., Sonenberg, Liz
Publikováno v:
In Artificial Intelligence January 2022 302
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 others. We point to recent work on social planning, i.e. planning in
Externí odkaz:
http://arxiv.org/abs/1602.06483
Autor:
Pearce, Adrian
Spatial interpretation involves the intelligent processing of images for learning, planning and visualisation. This involves building systems which learn to recognise patterns from the content of unconstrained data such as handwritten schematic symbo