1. vBattle: A new Framework to Simulate Medium-Scale Battles in Individual-per- Individual Basis L. Peña, J. M. Peña y S. Ossowski CIG – 2009 (Milan)

2. Index ➢ Objective ➢ Introduction ➢ vBattle. Framework ➢ vBattle. Computational Intelligence Application ➢ Conclusions and Future Work

3. Objective vBattle: new computational intelligence framework, for the evaluation of learning strategies in video games Simulates a battle game in which two or more contenders are fighting in units with a high-detail individual-per-individual resolution Simulates a battle game in which two or more contenders are fighting in units with a high-detail individual-per-individual resolution (1) actions parameters (action time, exhaustion consumption), (2) non-deterministic action resolution, (3) hierarchical intelligence (individual vs. unit strategies), and (4) scenario interaction

4. Introduction “AI Videogames world” What have we now? - Reusing old tailored algorithms. - Later stage of the game developments - Superb graphics → Mediocre AI What are we looking for? Use of new AI techniques applied to the videogame development.

5. Introduction We can use modding tools of existing game engine but … (1) does not provide a complete set of result analysis toolkits, (2) it presents a heavy-weight engine that does not support massive training needed for some algorithms and techniques, being evolutionary algorithms or reinforcement learning clear examples, and (3) the modding tools are limited in terms of customization or flexibility … or we could make one (1) Robocode (2) MiniGate (3) Nero 2.0

6. Introduction NERO 2.0 ● Great appeal ● Emergent behavior of the agent. ● Training and competition phases. ● User must interacts in the training. ● Only neural networks. ● Isn't open-source. ORTS ● Use a client/server architecture. ● Simple scripting language. ● Can connect different clients. ● AI pluggable components. ● RTS not suitable for trainin g

7. Introduction Lux Delux ● Use a client/server architecture. ● Unattended play / enabling training. ● Java SDK API for AI programming. ● Commercial, and not open-source. ● Very simple units and actions. ● Unique display mechanism. NWN Series ● Client/server architecture. ● Robust, supported by a company. ● Scripting language for AI. ● Actual commercial games. ● Commercial, and not open-source. ● No extensibility outside of the toolkit. ● RTS > no long training algorithms.

8. vBattle. Framework The vBATTLE framework has been designed following several principles and objectives : (1) Discrete event simulator (2) Parameters, actions and actors (3) Non-deterministic action system (4) Scenario interaction (5) Multilevel intelligence (5.1) Individual (5.2) Group (6) Decoupled Interface

9. vBattle. Framework vBattle Architecture

10. vBattle. Framework vBattle Components:

11. vBattle. Framework vBattle Technologies:

12. vBattle. Computational Intelligence Application vBattle Tournaments:

13. vBattle. Computational Intelligence Application vBattle Tournaments Types: ● One on One with Scenario ● Many on Many. Kill'em All ● Many on Many. Take the flag. “Very” Best Wishes.... – Make a competition scenario for the computer game AI research – “Very” Best Wishes.... – Make a competition scenario for the computer game AI research – vBattle Possible Research Scenarios: ● RL, Genetic Algorithm, … offline automatic strategy generation techniques. ● Multi-Level Decision Schemas on Strategy Games ● Introductory, Teaching AI environment.

14. Conclusions and Future Work Conclusions ● “Maybe is a good idea.... (maybe not...)” Questions ?????????? Future Work ● Almost everything! ● It's a first design for this framework ● Try different RL techniques in some other game (Robosoccer or ORTS) for validation