Diego Pérez-Liébana

research

∙ 07/19/2023

PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games

In recent years, Game AI research has made important breakthroughs using...

0 Martin Balla, et al. ∙

research

∙ 05/30/2022

Elastic Monte Carlo Tree Search with State Abstraction for Strategy Game Playing

Strategy video games challenge AI agents with their combinatorial search...

0 Linjie Xu, et al. ∙

research

∙ 05/20/2022

Task Relabelling for Multi-task Transfer using Successor Features

Deep Reinforcement Learning has been very successful recently with vario...

5 Martin Balla, et al. ∙

research

∙ 02/11/2022

Visualising Multiplayer Game Spaces

We compare four different `game-spaces' in terms of their usefulness in ...

32 James Goodman, et al. ∙

research

∙ 04/21/2021

Portfolio Search and Optimization for General Strategy Game-Playing

Portfolio methods represent a simple but efficient type of action abstra...

0 Alexander Dockhorn, et al. ∙

research

∙ 04/17/2021

Generating Diverse and Competitive Play-Styles for Strategy Games

Designing agents that are able to achieve different play-styles while ma...

0 Diego Pérez-Liébana, et al. ∙

research

∙ 04/17/2021

Action Advising with Advice Imitation in Deep Reinforcement Learning

Action advising is a peer-to-peer knowledge exchange technique built on ...

0 Ercüment İlhan, et al. ∙

research

∙ 04/17/2021

Learning on a Budget via Teacher Imitation

Deep Reinforcement Learning (RL) techniques can benefit greatly from lev...

0 Ercüment İlhan, et al. ∙

research

∙ 10/01/2020

Student-Initiated Action Advising via Advice Novelty

Action advising is a knowledge exchange mechanism between peers, namely ...

3 Ercüment İlhan, et al. ∙

research

∙ 09/25/2020

Design and Implementation of TAG: A Tabletop Games Framework

This document describes the design and implementation of the Tabletop Ga...

10 Raluca D. Gaina, et al. ∙

research

∙ 09/18/2020

TotalBotWar: A New Pseudo Real-time Multi-action Game Challenge and Competition for AI

This paper presents TotalBotWar, a new pseudo real-time multi-action cha...

11 Alejandro Estaben, et al. ∙

research

∙ 09/11/2020

The Design Of "Stratega": A General Strategy Games Framework

Stratega, a general strategy games framework, has been designed to foste...

19 Diego Pérez-Liébana, et al. ∙

research

∙ 05/22/2020

Evaluating Generalisation in General Video Game Playing

The General Video Game Artificial Intelligence (GVGAI) competition has b...

1 Martin Balla, et al. ∙

research

∙ 05/14/2020

Rolling Horizon NEAT for General Video Game Playing

This paper presents a new Statistical Forward Planning (SFP) method, Rol...

1 Diego Pérez-Liébana, et al. ∙

research

∙ 05/12/2020

Guaranteeing Reproducibility in Deep Learning Competitions

To encourage the development of methods with reproducible and robust tra...

3 Brandon Houghton, et al. ∙

research

∙ 03/27/2020

Rolling Horizon Evolutionary Algorithms for General Video Game Playing

Game-playing Evolutionary Algorithms, specifically Rolling Horizon Evolu...

4 Raluca D. Gaina, et al. ∙

research

∙ 09/01/2019

Learning Local Forward Models on Unforgiving Games

This paper examines learning approaches for forward models based on loca...

4 Alexander Dockhorn, et al. ∙

research

∙ 06/12/2019

General Video Game Rule Generation

We introduce the General Video Game Rule Generation problem, and the epo...

10 Ahmed Khalifa, et al. ∙

research

∙ 06/10/2019

Project Thyia: A Forever Gameplayer

The space of Artificial Intelligence entities is dominated by conversati...

5 Raluca D. Gaina, et al. ∙

research

∙ 05/26/2019

Ensemble Decision Systems for General Video Game Playing

Ensemble Decision Systems offer a unique form of decision making that al...

1 Damien Anderson, et al. ∙

research

∙ 04/22/2019

The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors

Though deep reinforcement learning has led to breakthroughs in many diff...

10 William H. Guss, et al. ∙

research

∙ 04/19/2019

Teaching on a Budget in Multi-Agent Deep Reinforcement Learning

Deep Reinforcement Learning algorithms can solve complex sequential deci...

0 Ercüment İlhan, et al. ∙

research

∙ 04/03/2019

Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor

Game-based benchmarks have been playing an essential role in the develop...

10 Ivan Bravi, et al. ∙

research

∙ 03/29/2019

A Local Approach to Forward Model Learning: Results on the Game of Life Game

This paper investigates the effect of learning a forward model on the pe...

8 Simon M. Lucas, et al. ∙

research

∙ 01/23/2019

The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition

Learning in multi-agent scenarios is a fruitful research direction, but ...

12 Diego Pérez-Liébana, et al. ∙

research

∙ 01/03/2019

Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is Best

This paper introduces a simple and fast variant of Planet Wars as a test...

20 Simon M. Lucas, et al. ∙

research

∙ 06/06/2018

Deep Reinforcement Learning for General Video Game AI

The General Video Game AI (GVGAI) competition and its associated softwar...

12 Ruben Rodriguez Torrado, et al. ∙

research

∙ 06/04/2018

Shallow decision-making analysis in General Video Game Playing

The General Video Game AI competitions have been the testing ground for ...

0 Ivan Bravi, et al. ∙

research

∙ 02/28/2018

General Video Game AI: a Multi-Track Framework for Evaluating Agents, Games and Content Generation Algorithms

General Video Game Playing (GVGP) aims at designing an agent that is cap...

0 Diego Pérez-Liébana, et al. ∙

research

∙ 02/16/2018

The N-Tuple Bandit Evolutionary Algorithm for Game Agent Optimisation

This paper describes the N-Tuple Bandit Evolutionary Algorithm (NTBEA), ...

0 Simon M. Lucas, et al. ∙

research

∙ 08/07/2017

Efficient Noisy Optimisation with the Sliding Window Compact Genetic Algorithm

The compact genetic algorithm is an Estimation of Distribution Algorithm...

0 Simon M. Lucas, et al. ∙

research

∙ 06/13/2017

Evaluating Noisy Optimisation Algorithms: First Hitting Time is Problematic

A key part of any evolutionary algorithm is fitness evaluation. When fit...

0 Simon M. Lucas, et al. ∙

research

∙ 04/24/2017

Analysis of Vanilla Rolling Horizon Evolution Parameters in General Video Game Playing

Monte Carlo Tree Search techniques have generally dominated General Vide...

0 Raluca D. Gaina, et al. ∙

research

∙ 04/24/2017

Evaluating and Modelling Hanabi-Playing Agents

Agent modelling involves considering how other agents will behave, in or...

0 Joseph Walton-Rivers, et al. ∙

research

∙ 04/23/2017

General Video Game AI: Learning from Screen Capture

General Video Game Artificial Intelligence is a general game playing fra...

0 Kamolwan Kunanusont, et al. ∙

research

∙ 04/23/2017

Population Seeding Techniques for Rolling Horizon Evolution in General Video Game Playing

While Monte Carlo Tree Search and closely related methods have dominated...

0 Rauca D. Gaina, et al. ∙

research

∙ 09/08/2016

Ms. Pac-Man Versus Ghost Team CIG 2016 Competition

This paper introduces the revival of the popular Ms. Pac-Man Versus Ghos...

0 Piers R. Williams, et al. ∙

research

∙ 07/22/2016

Optimal resampling for the noisy OneMax problem

The OneMax problem is a standard benchmark optimisation problem for a bi...

0 Jialin Liu, et al. ∙

research

∙ 07/06/2016

Rolling Horizon Coevolutionary Planning for Two-Player Video Games

This paper describes a new algorithm for decision making in two-player r...

0 Jialin Liu, et al. ∙

research

∙ 06/20/2016

Bandit-Based Random Mutation Hill-Climbing

The Random Mutation Hill-Climbing algorithm is a direct search technique...

0 Jialin Liu, et al. ∙

Diego Pérez-Liébana

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