Search Results for author: Ryan Spick

Found 3 papers, 1 papers with code

Time to Die: Death Prediction in Dota 2 using Deep Learning

1 code implementation21 May 2019 Adam Katona, Ryan Spick, Victoria Hodge, Simon Demediuk, Florian Block, Anders Drachen, James Alfred Walker

Even though death events are rare within a game (1\% of the data), the model achieves 0. 377 precision with 0. 725 recall on test data when prompted to predict which of any of the 10 players of either team will die within 5 seconds.

Dota 2

Behavioural Cloning in VizDoom

no code implementations8 Jan 2024 Ryan Spick, Timothy Bradley, Ayush Raina, Pierluigi Vito Amadori, Guy Moss

This paper describes methods for training autonomous agents to play the game "Doom 2" through Imitation Learning (IL) using only pixel data as input.

Behavioural cloning Reinforcement Learning (RL)

Robust Imitation Learning for Automated Game Testing

no code implementations9 Jan 2024 Pierluigi Vito Amadori, Timothy Bradley, Ryan Spick, Guy Moss

Game development is a long process that involves many stages before a product is ready for the market.

Behavioural cloning Navigate

Cannot find the paper you are looking for? You can Submit a new open access paper.