speaker-info

Mihail Morosan

PhD Student, Essex

Biography

Programmer (with a focus on optimisation and quick deliverables, mostly due to competitive experience), gamer (games are fun, relaxing and a great social experience), technology consumer (comes with the programmer bit) and all around happy guy stumbling through the world. Once ended up in a management internship at a bank thinking the application was for a programming position. And another time told an interviewer that “buying and eating a burger to solve hunger” is a legitimate problem-solving skill. Somehow received an invitation to the next interview stage.

Thesis

Computational Intelligence and Game Balance

Game design has been a staple of human ingenuity and innovation for as long as games have been around. From sports, such as football, to applying game mechanics to the real world, such as reward schemes in shops, games have impacted the world in surprising ways. This process can, and should, be aided by automated systems, as machines have proven to be capable of finding innovative ways to complement human intuition and inventiveness.

When man and machine cooperate, better products are created and the world has only to benefit. My research seeks to find, test and assess methods to apply computational intelligence to human-led game balance. Results so far have proven that AI can successfully aid game designers in analysing the viability of various game rules and I intend to document this and polish the techniques that will result from my work. To achieve this, I am making use of cutting edge algorithms, powerful AI techniques and novel methods, but also industry feedback. Most of the current work done involves the use of evolutionary algorithms, as well as statistical analysis and evaluation of intelligent agents in various video games.

Skills

  • C#, C++, Pascal, JavaScript, Python, Ruby and more
  • Unity game development as well as Irrlicht 3D
  • Participated in lots of programming competitions with a focus on solving tasks with optimal solutions in minimal time
  • Decent at Magic: the Gathering

Details

Home Institution: University of Essex
Supervisors: Riccardo Poli (Essex) and Daniel Kudenko (York)
Email: mmoros@essex.ac.uk
Twitter@MorosanMihail
LinkedIn: https://uk.linkedin.com/in/morosanmihail
Web: http://www.morosanmihail.com/

My Sessions

Workshop: How to Train a Balanced AI Agent

Get hands-on with graphical UI tools for rapid game AI prototyping and balancing

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