First Seminar Presentation

ADAPTIVE INTELLIGENT AGENT IN REAL-TIME STRATEGY GAMES

An Introduction

PROJECT MEMBERS

Omar Enayet

Amr Saqr

Ahmed Atta

Abdelrahman Al-Ogail

Dr. Mostafa Aref

Dr. Ibrahim Fathy

AGENDA

Problem Definition Theoretical Areas of Problem. Project Domain. Specific Problem Definition.

Motivations. Objectives. Project Background

Survey & Approach. Domain Platform. AI Engine Architecture.

Expected Deliverables. Development Tools. Project Time Plan. Web Resources & References.

THEORETICAL AREAS

LearningMake the machine learn.

THEORETICAL AREAS

PlanningPlan then re-plan according to new givens.

THEORETICAL AREAS

Knowledge SharingLet everyone know instantly what you knew through experience.

THEORETICAL AREAS - SUMMARY

LearningPlanningKnowledge Sharing

PROJECT DOMAIN

RTS GamesReal-Time Strategy Games.

PROBLEM DEFINITION

PredictabilityComputer Opponent actions easily predicted.

PROBLEM DEFINITION

Non-AdaptabilityComputer Opponent doesn’t adapt to changes in human actions.

PROBLEM DEFINITION

Static ScriptsComputer AI relies on static scripting techniques.

PROBLEM DEFINITION

Experience LossThe Absence of sharing experience costs a lot.

PROBLEM DEFINITION - SUMMARY

PredictabilityNon-AdaptabilityStatic Scripting Experience Loss

MOTIVATIONS

InterestedIn Machine Learning

MOTIVATIONS

InterestedIn RTS Games

MOTIVATIONS

MeetsOur Career Ambitions as AI Programmers

WHY THIS DOMAIN

Rich Environment.

Severe Time Constraints – Real-Time AI – Many Objects – Imperfect Information – Micro-Actions

WHY THIS DOMAIN

Active ResearchTheses and Papers are from 2003 to 2009.

WHY THIS DOMAIN

Wars SimulationResearch in this field contributes to the modern warfare Research.

Half of The USA’s Army will be robots in the coming years.

OBJECTIVES

Adaptive A.I.Making the Computer Opponent adapt to changes like human do.

OBJECTIVES

Mobile Experience

Making Sharing Experience Possible Among Machines

SURVEY

Recent PapersWe Collected more than 30 papers concerning this field, different in their way of approaching the problem and the techniques used to

solve the problem. Examples of them are above ^

•Adaptive Reinforcement Learning Agents in RTS Games

•Case-based planning and execution for real-time strategy games.

•Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL

SURVEY

Asking ExpertsAlex Champandard, Eric Kok and more.

Alex Champandard Eric Kok

SURVEY

Reference BookThe Book “AI Game Engine Programming” talks about the drawbacks

in learning and planning in RTS Games.

APPROACHES - TECHNIQUES

Reinforcement LearningA Sub-Science of Machine Learning.


Case-Based PlanningPlanning using Case-based reasoning.


BDI Agents Tech.Beliefs-Desires-Intentions Agents.

TECHNIQUES - SUMMARY

Reinforcement Learning

Case-Based PlanningBDI-Agent Tech.

APPROACHES - LANGUAGES

C++The Main Language our Open Source Game is coded with.


2APLAn Agent-Oriented Language.


LUAA Scripting Language widely used in Video-Games.

PLATFORM – NOT CHOSEN

ORTSAn Open-Source RTS Game

PLATFORM – NOT CHOSEN

WargusAn Open-Source RTS Game based in Stratagus Game Engine

PLATFORM – THE CHOSEN ONE

BosWarsAn Open-Source RTS Game based in Stratagus Game Engine

PROJECT TIME PLAN

Specifying project problem

Survey on recent research

Building background in general Game AI

Searching for open-source platform

Developing UML of BosWars

Building background on Machine Learning techniques

Developing a framework for each technique

Integrating techniques within platform

Testing

Documentation

1-Sep-09 21-Oct-09 10-Dec-09 29-Jan-10 20-Mar-10 9-May-10

GAME ENGINE

AIEngine

That’s our guy

AI ENGINE ARCHITECTURE

EXPECTED DELIVERABLES

Enhanced AI EngineAn AI Engine which makes the computer behavior in the game as

human as possible.

EXPECTED DELIVERABLES

Experimental ResultsComparison of the results of the enhanced AI Engine with ordinary

static AI.

Visual Studio 2008 Professional Edition

2APL Environment C++ Libraries : Boost, Guichan ..etc.

DEVELOPMENT TOOLS

Project Blog : http://rtsairesearch.wordpress.com/

SVN Repository : https://mzrtaiengine.googlecode.com/svn/trunk/

WEB RESOURCES

Book : AI Game Engine Programming Book : Artificial Intelligence for Games The Most Important Papers/Theses :

Thanks

REFERENCES

•Eric Kok - Adaptive Reinforcement Learning Agents in RTS Games –– Master Thesis – University of Utrecht - 2008

•Santi Onta˜n´on, Kinshuk Mishra, Neha Sugandh, and Ashwin Ram. Case-basedplanning and execution for real-time strategy games. In Proceedings of ICCBR - 2007 - 2007

•Manu Sharma, Michael Holmes, Juan Carlos Santamaria, Arya Irani, Charles Lee Isbell Jr., Ashwin Ram: Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL. IJCAI 2007: 1041-1046

WEB REFERENCES

http://gadgets.softpedia.com/news/US-Soldiers-Will-be-Half-Robots-Half-Human-by-2015-1334-01.html

http://www.france24.com/en/20090205-sciences-usa-robot-future-american-army-videogame-soldiers-machine

First Seminar Presentation

Education

Transcript of First Seminar Presentation