Diverse, Top-k, and Top-Quality Planning Over Simulators

no code implementations • 25 Aug 2023 • Lyndon Benke, Tim Miller, Michael Papasimeon, Nir Lipovetzky

Diverse, top-k, and top-quality planning are concerned with the generation of sets of solutions to sequential decision problems.

Multi-Agent Simulation for AI Behaviour Discovery in Operations Research

no code implementations • 30 Aug 2021 • Michael Papasimeon, Lyndon Benke

We describe ACE0, a lightweight platform for evaluating the suitability and viability of AI methods for behaviour discovery in multiagent simulations.

Text Generation with Deep Variational GAN

no code implementations • 27 Apr 2021 • Mahmoud Hossam, Trung Le, Michael Papasimeon, Viet Huynh, Dinh Phung

Generating realistic sequences is a central task in many machine learning applications.

Text Generation

Discrete-to-Deep Supervised Policy Learning

1 code implementation • 5 May 2020 • Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale

It then selects from each discrete state an input value and the action with the highest numerical preference as an input/target pair.

Reinforcement Learning (RL)

OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation

1 code implementation • 16 Apr 2020 • Mahmoud Hossam, Trung Le, Viet Huynh, Michael Papasimeon, Dinh Phung

One of the challenging problems in sequence generation tasks is the optimized generation of sequences with specific desired goals.

reinforcement-learning Reinforcement Learning (RL)