Tag Archives: Genetic Algorithms

Dangerousness Metric for Gene Regulated Car Driving

13 Apr

Paper presented as interactive talk and poster at EvoGAMES 2016 in Porto (Portugal).

BY:
Sylvain Cussat-Blanc, Jean Disset, Stephane Sanchez

ABSTRACT:

In this paper, we show how a dangerousness metric can be used to modify the input of a gene regulatory network when plugged to a virtual car. In the context of the 2015 Simulated Car Racing Championship organized during GECCO 2015, we have developed a new cartography methodology able to inform the controller of the car about the incoming complexity of the track: turns (slipperiness, angle, etc.) and bumps. We show how this dangerousness metric improves the results of our controller and outperforms other approaches on the tracks used in the competition.

PRESENTATION:

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https://www.irit.fr/~Sylvain.Cussat-Blanc/shared/slides_evostar16.pdf

Enjoy it!

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Unreal Expert Bots at IWANN 2013

20 Jun

Last week there was held IWANN 2013 at Tenerife, an international conference mainly devoted to researches inside the neural networks scope. In it, Antonio Fernández Leiva, Raúl Lara and Me organized the Special Session on Artificial Intelligence and Games.

There were five works in the session, one of them “Designing and Evolving an Unreal Tournament— 2004 Expert Bot“.

It describes the designing and improvement, through off-line (not during the game) evolution, of an autonomous agent (or bot) for playing the game Unreal Tournament 2004. This was created by means of a finite state machine which models the expert behaviour of a human player in 1 vs 1 deathmatch mode, following the rules of the international competition.

Then, the bot was improved by means of a Genetic Algorithm, yielding an agent that is, in turn a very hard opponent for the medium-level human player and which can (easily) beat the default bots in the game, even in the maximum difficulty level.

The presentation can be seen at:

Moreover, you can watch one example of the evolution in the following video:

Finally, the Unreal Expert and Genetic bot’s source code are available at https://github.com/franaisa/ExpertAgent

Enjoy them. 😉

Super Mario Evolutionary FSM-Based Agent

17 Apr

Recently, inside the last LION 7 (2013) conference (Special Session on Games and Computational Intelligence) there was presented the paper entitled “FSM-Based Agents for Playing Super Mario Game”.

It describes the implementation and test of an autonomous agent which can play Super Mario game better than an expert user can do (in some trained levels).
It is build starting from a Finite State Machine and applying an Evolutionary Algorithm.

The presentation is:

You can watch one example of the obtained agent playing a game here:

Enjoy it. 😉