27 citations · 66 across the 29 of their papers we have counts for
36 papers
Evidence-Gated Task and Motion Planning with Vision-Language Models
Tsunehiko Tanaka, Matthew Stephenson, Alistair Macvicar +1
Robots executing long-horizon manipulation tasks from natural-language instructions must reason about both semantic task structure and geometric feasibility. However, under partial…
Best Agent Identification for General Game Playing
Matthew Stephenson, Alex Newcombe, Eric Piette +1
We present an efficient and generalised procedure to accurately identify the best (or near best) performing algorithm for each sub-task in a multi-problem domain. Our approach trea…
An Ambiguous State Machine
Matt Stephenson
We show that a replicated state machine (such as a blockchain protocol) can retain liveness in a strategic setting even while facing substantial ambiguity over certain events. This…
NDAI Agreements
Matthew Stephenson, Andrew Miller, Xyn Sun +2
We study a fundamental challenge in the economics of innovation: an inventor must reveal details of a new idea to secure compensation or funding, yet such disclosure risks expropri…
Towards Bio-inspired Heuristically Accelerated Reinforcement Learning for Adaptive Underwater Multi-Agents Behaviour
Antoine Vivien, Thomas Chaffre, Matthew Stephenson +4
This paper describes the problem of coordination of an autonomous Multi-Agent System which aims to solve the coverage planning problem in a complex environment. The considered appl…
GAVEL: Generating Games Via Evolution and Language Models
Graham Todd, Alexander Padula, Matthew Stephenson +3
Automatically generating novel and interesting games is a complex task. Challenges include representing game rules in a computationally workable form, searching through the large s…
Cooperative AI via Decentralized Commitment Devices
Xinyuan Sun, Davide Crapis, Matt Stephenson +3
Credible commitment devices have been a popular approach for robust multi-agent coordination. However, existing commitment mechanisms face limitations like privacy, integrity, and…
Utilizing Generative Adversarial Networks for Stable Structure Generation in Angry Birds
Frederic Abraham, Matthew Stephenson
This paper investigates the suitability of using Generative Adversarial Networks (GANs) to generate stable structures for the physics-based puzzle game Angry Birds. While previous…
Physics-Based Task Generation through Causal Sequence of Physical Interactions
Chathura Gamage, Vimukthini Pinto, Matthew Stephenson +1
Performing tasks in a physical environment is a crucial yet challenging problem for AI systems operating in the real world. Physics simulation-based tasks are often employed to fac…
NovPhy: A Testbed for Physical Reasoning in Open-world Environments
Chathura Gamage, Vimukthini Pinto, Cheng Xue +4
Due to the emergence of AI systems that interact with the physical environment, there is an increased interest in incorporating physical reasoning capabilities into those AI system…
Measuring Board Game Distance
Matthew Stephenson, Dennis J. N. J. Soemers, Éric Piette +1
This paper presents a general approach for measuring distances between board games within the Ludii general game system. These distances are calculated using a previously published…
The Ludii Game Description Language is Universal
Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson +1
There are several different game description languages (GDLs), each intended to allow wide ranges of arbitrary games (i.e., general games) to be described in a single higher-level…
Spatial State-Action Features for General Games
Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson +1
In many board games and other abstract games, patterns have been used as features that can guide automated game-playing agents. Such patterns or features often represent particular…
General Board Geometry
Cameron Browne, Éric Piette, Matthew Stephenson +1
Game boards are described in the Ludii general game system by their underlying graphs, based on tiling, shape and graph operators, with the automatic detection of important propert…
Optimised Playout Implementations for the Ludii General Game System
Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson +1
This paper describes three different optimised implementations of playouts, as commonly used by game-playing algorithms such as Monte-Carlo Tree Search. Each of the optimised imple…
Automatic Generation of Board Game Manuals
Matthew Stephenson, Eric Piette, Dennis J. N. J. Soemers +1
In this paper we present a process for automatically generating manuals for board games within the Ludii general game system. This process requires many different sub-tasks to be a…
General Board Game Concepts
Éric Piette, Matthew Stephenson, Dennis J. N. J. Soemers +1
Many games often share common ideas or aspects between them, such as their rules, controls, or playing area. However, in the context of General Game Playing (GGP) for board games,…
Deceptive Level Generation for Angry Birds
Chathura Gamage, Matthew Stephenson, Vimukthini Pinto +1
The Angry Birds AI competition has been held over many years to encourage the development of AI agents that can play Angry Birds game levels better than human players. Many differe…
General Game Heuristic Prediction Based on Ludeme Descriptions
Matthew Stephenson, Dennis J. N. J. Soemers, Eric Piette +1
This paper investigates the performance of different general-game-playing heuristics for games in the Ludii general game system. Based on these results, we train several regression…
Transfer of Fully Convolutional Policy-Value Networks Between Games and Game Variants
Dennis J. N. J. Soemers, Vegard Mella, Eric Piette +3
In this paper, we use fully convolutional architectures in AlphaZero-like self-play training setups to facilitate transfer between variants of board games as well as distinct games…
Manipulating the Distributions of Experience used for Self-Play Learning in Expert Iteration
Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson +1
Expert Iteration (ExIt) is an effective framework for learning game-playing policies from self-play. ExIt involves training a policy to mimic the search behaviour of a tree search…
Superstition in the Network: Deep Reinforcement Learning Plays Deceptive Games
Philip Bontrager, Ahmed Khalifa, Damien Anderson +3
Deep reinforcement learning has learned to play many games well, but failed on others. To better characterize the modes and reasons of failure of deep reinforcement learners, we te…
Ludii as a Competition Platform
Matthew Stephenson, Éric Piette, Dennis J. N. J. Soemers +1
Ludii is a general game system being developed as part of the ERC-funded Digital Ludeme Project (DLP). While its primary aim is to model, play, and analyse the full range of tradit…
Ludii and XCSP: Playing and Solving Logic Puzzles
Cédric Piette, Éric Piette, Matthew Stephenson +2
Many of the famous single-player games, commonly called puzzles, can be shown to be NP-Complete. Indeed, this class of complexity contains hundreds of puzzles, since people particu…