3 papers
cs.LG2026
Gradient-Based Program Synthesis with Neurally Interpreted Languages
Matthew V. Macfarlane, Clément Bonnet, Herke van Hoof +1
A central challenge in program induction has long been the trade-off between symbolic and neural approaches. Symbolic methods offer compositional generalisation and data efficiency…
cs.LG2024
Searching Latent Program Spaces
Matthew V Macfarlane, Clement Bonnet
General intelligence requires systems that acquire new skills efficiently and generalize beyond their training distributions. Although program synthesis approaches have strong gene…
cs.AI2024
SPO: Sequential Monte Carlo Policy Optimisation
Matthew V Macfarlane, Edan Toledo, Donal Byrne +2
Leveraging planning during learning and decision-making is central to the long-term development of intelligent agents. Recent works have successfully combined tree-based search met…