Graham Kendall
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Professor Graham Kendall

Professor Graham Kendall is the Provost and CEO of The University of Nottingham Malaysia Campus (UNMC). He is also a Pro-Vice Chancellor of the University of Nottingham.

He is a Director of MyResearch Sdn Bhd, Crops for the Future Sdn Bhd. and Nottingham Green Technologies Sdn Bhd. He is a Fellow of the British Computer Society (FBCS) and a Fellow of the Operational Research Society (FORS).

He has published over 230 peer reviewed papers. He is an Associate Editor of 10 journals and the Editor-in-Chief of the IEEE Transactions of Computational Intelligence and AI in Games.

News

Does AI have a place in the board room?
http://bit.ly/1DXreuW
I am involved with a spin out company that specialises in Strategic Resource Planning
http://bit.ly/eTPZO2

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Conjuring Trick: Revealed

Publication(s)

Scripting the Game of Lemmings with a Genetic Algorithm
http://bit.ly/g0igy0
Hyperheuristics: A Robust Optimisation Method Applied to Nurse Scheduling
http://bit.ly/h17mwh
Throughput Maximization of Queueing Networks with Simultaneous Minimization of Service Rates and Buffers
http://bit.ly/1cJuWLM
Applying Simulated Annealing and the No Fit Polygon to the Nesting Problem
http://bit.ly/ikrub2

Graham Kendall: Details of Requested Publication


Citation

Levine, J; Congdon, C. B.; Ebner, M; Kendall, G; Lucas, S.M.; Miikkulainen, R; Schaul, T and Thompson, T General Video Game Playing. In Artificial and Computational Intelligence in Games: A Follow-up to Dagstuhl Seminar 12191, pages 77-83, 2012.

This was a follow up publication to a Dagstuhl seminar


Abstract

tasks, not just one. In the area of games, this has given rise to the challenge of General Game Playing (GGP). In GGP, the game (typically a turn-taking board game) is defined declaratively in terms of the logic of the game (what happens when a move is made, how the scoring system works, how the winner is declared, and so on). The AI player then has to work out how to play the game and how to win. In this work, we seek to extend the idea of General Game Playing into the realm of video games, thus forming the area of General Video Game Playing (GVGP). In GVGP, computational agents will be asked to play video games that they have not seen before. At the minimum, the agent will be given the current state of the world and told what actions are applicable. Every game tick the agent will have to decide on its action, and the state will be updated, taking into account the actions of the other agents in the game and the game physics. We envisage running a competition based on GVGP playing, using arcade-style (e.g. similar to Atari 2600) games as our starting point. These games are rich enough to be a formidable challenge to a GVGP agent, without introducing unnecessary complexity. The competition that we envisage could have a number of tracks, based on the form of the state (frame buffer or object model) and whether or not a forward model of action execution is available. We propose that the existing Physical Travelling Salesman (PTSP) software could be extended for our purposes and that a variety of GVGP games could be created in this framework by AI and Games students and other developers. Beyond this, we envisage the development of a Video Game Description Language (VGDL) as a way of concisely specifying video games. For the competition, we see this as being an interesting challenge in terms of deliberative search, machine learning and transfer of existing knowledge into new domains.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.4230/DFU.Vol6.12191.77 You can link directly to the original paper, via the doi, from here

What is a doi?: A doi (Document Object Identifier) is a unique identifier for sicientific papers (and occasionally other material). This provides direct access to the location where the original article is published using the URL http://dx.doi/org/xxxx (replacing xxx with the doi). See http://dx.doi.org/ for more information



URL

The URL for additional information is http://drops.dagstuhl.de/portals/dfu/index.php?semnr=13017

The URL is only provided if there is additional information that might be useful. For example, where the entry is a book chapter, the URL might link to the book itself.


Bibtex

@INBOOK{lbeklmst2012, chapter = {Artificial and Computational Intelligence in Games: A Follow-up to Dagstuhl Seminar 12191},
pages = {77--83},
title = {General Video Game Playing},
year = {2012},
editor = {S.M. Lucas and M. Mateas and M. Preuss and P. Spronck and J. Togelius},
author = {J. Levine and C. Bates Congdon and M. Ebner and G. Kendall and S.M. Lucas and R. Miikkulainen and T. Schaul and T. Thompson},
volume = {6},
note = {This was a follow up publication to a Dagstuhl seminar},
abstract = {tasks, not just one. In the area of games, this has given rise to the challenge of General Game Playing (GGP). In GGP, the game (typically a turn-taking board game) is defined declaratively in terms of the logic of the game (what happens when a move is made, how the scoring system works, how the winner is declared, and so on). The AI player then has to work out how to play the game and how to win. In this work, we seek to extend the idea of General Game Playing into the realm of video games, thus forming the area of General Video Game Playing (GVGP). In GVGP, computational agents will be asked to play video games that they have not seen before. At the minimum, the agent will be given the current state of the world and told what actions are applicable. Every game tick the agent will have to decide on its action, and the state will be updated, taking into account the actions of the other agents in the game and the game physics. We envisage running a competition based on GVGP playing, using arcade-style (e.g. similar to Atari 2600) games as our starting point. These games are rich enough to be a formidable challenge to a GVGP agent, without introducing unnecessary complexity. The competition that we envisage could have a number of tracks, based on the form of the state (frame buffer or object model) and whether or not a forward model of action execution is available. We propose that the existing Physical Travelling Salesman (PTSP) software could be extended for our purposes and that a variety of GVGP games could be created in this framework by AI and Games students and other developers. Beyond this, we envisage the development of a Video Game Description Language (VGDL) as a way of concisely specifying video games. For the competition, we see this as being an interesting challenge in terms of deliberative search, machine learning and transfer of existing knowledge into new domains.},
doi = {10.4230/DFU.Vol6.12191.77},
owner = {Graham},
timestamp = {2013.12.27},
url = {http://drops.dagstuhl.de/portals/dfu/index.php?semnr=13017},
webpdf = {http://www.graham-kendall.com/papers/lbeklmst2012.pdf} }