Ontologies Reasoning Components Agents Simulations RARCS/ESOA/MDA Unified Project Topics 2009.1 Jacques Robin.

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Presentation transcript:

Ontologies Reasoning Components Agents Simulations RARCS/ESOA/MDA Unified Project Topics Jacques Robin

AOCBMDE Case Study: Rollerslam Simulation  Application 1: Fully Customizable Games  Innovative software process for fast prototyping fully customizable games where the user changes the field, the rules etc.  Allows use of focus groups too define most exciting rule sets for games based on imaginary, science-fiction sports  Allows the Web2.0 evolutions of game variations and community based emergence of the most popular sets of rules  Application 2: Workbench for Controlled Experiments to Comparatively Evaluate Multi-Agent Systems: 1.MAS architecture 2.Communication, cooperation and competition protocols 3.Internal architecture of each agent 4.Automated reasoning task of each component of a given internal architecture 5.Knowledge representation language of each component of a given internal architecture 6.Agent team strategies 7.Software process  Full customization of environment characteristics (observability, determinism, dynamicity, continuity, etc.) for a given set of rules

AOCBMDE Case Study: Rollerslam Simulation  Application 3: Tutorial System for Agents and Automated Reasoning  Fully customizable environment allowing students to build agents and test agents and agent teams for most possible combinations of environment characteristics  Link to Wiki pages with didactic material about societal and agent internal architectures, automated reasoning tasks and knowledge representation languages  Built-in societal and agent internal architectural patterns to be selected from a menu  Built-in component-based object-oriented rule-based knowledge representation language (COFL) and associated inference engine (COFLUX)  Students introduced to gradually more sophisticated:  Environments, all different versions of a single, unifying domain (Rollerslam sport simulation)  Societal and agent internal architectures  Automated reasoning tasks and knowledge representation language

Rollerslam: A Futuristic Fusion Sport Rollerslam! Soccer Handball Ice Hockey Australian Football Basketball Rugby Gaelic Football American Football Roller Derby Slamball

Rollerslam: The Sport 78m 16m 64,25m 45m 24m Field in-track out-track Ramp Edge Trampoline Goal In-Tramp Out-Tramp Center Circle Bounce Circle Track Zone Division

Rollerslam: The Sport

Inner Trampoline Goal Ramp Outer Trampoline (Ramp) Edge Basket Edge Shot Square Goal Line Edge Wall Field Offensive Edge Shot Circle Defensive Edge Shot Circle

Rollerslam: The Sport 7m 10m 2.5m 3m 6m 4m 5m 7m 1.25m 1.5m 3m

Rollerslam: The Sport 7m

Rollerslam: The Sport  Low Goal:  Touched close hand: 1 pt  Clear close hand, touched close foot, touched far hand, touched close hand volley: 2 pts  Clear close foot, clear far hand, clear close hand volley: 4 pts  Try: 7 pts  Clear far foot, clear close foot volley: 8 pts  Clear far foot volley: 16 pts  High Goal:  Close hand high volley: 1 pt  Close hand high goal: 2 pts  Close foot high volley: 3 pts  Close foot high goal: 4 pts  Far foot high volley: 6 pts  Far high goal: 16 pts  Baskets:  Front tramp hand hoop, simple dunk: 4 pts  Front ramp hand hoop, front alley dunk: 6 pts  Back tramp hand hoop, far dunk: 8 pts  Back ramp hand hoop, back alley dunk, front far hand hoop, front tramp foot hoop: 12 pts  Front ramp foot hoop: 18 pts  Back far hand hoop, back tramp foot hoop: 24 pts  Front track hand hoop: 36 pts  Back track hand hoop, front track foot hoop: 72 pts  Back track foot hoop: 144 pts  Laps:  1 passing lap: 16 pts  N consecutive passing laps: (N+1)*16 pts  1 rushing lap: 32 pts  N consecutive rushing laps: (N+1)*32 pts

Tactics: the Line-Up BT 1 GK 0 RB 2 LB 3 CB 4 FB 5 FB 6 HB 8 RT 7 QB 9 LT 11 HF 10 RV 12 RV 13 CF 15 RF 14 LF 16 FT 19 FF 17 FF 18 IB 20 IT 21 IR 22 IC 23 IF 24

PenaltySim: The Minimum Toy Multi- Agent Simulation 3 2k 1s, b Y X bk 1s Y X 123 3b 2k 1s Y X 123 action(s,legs,shoot(2)) action(k,legs,move(right)) 3 2k, b 1s Y X 123 action(k,hands,grab(yes)) 3 2k, b 1s Y X 123 gameOver, goal gameOver, nogoal action(s,legs,shoot(3)) action(k,legs,move(right)) actions(k,legs,move(right))

Infra-Structure Modeling and Implementing Tasks 1.Agent-Oriented KobrA2 Modeling Framework (Eric et al.)  a) Specify Object-Oriented Fluent Calculus in UML/OCL (OOFC, Eric), 10/06  b) KobrA2 PIM of Internal Agent Architecture (Eric, Ramon, Marcellus), 17/06  c) KobrA2 Multi-Agent Simulation PIM Framework (KMAPF, Eric), 24/06  d) Java (?) Implementation of MAS PIM Framework (Eric, Peterson), 08/07 2.Agent-Oriented Implementation Platform (Cleyton)  a) Port CHORD to CHROME, 10/06  b) Implement OOFC in CHORD, 17/06  c) Implement Agent PIM Framework in CHORD (OOFC-based belief revision + CHORD based action strategy), 08/07 3.3D Animation KobrA2 Modeling Framework (Peterson)  a) KobrA2 PIM of Java 3D e Direct 3D (others free platforms better candidates?) 17/06

Infra-Structure Preliminary Toy Testing Tasks 4.PenaltySim PIM as Instance of KMAPF (Eric, Peterson) 01/07 5.PenaltySim GamePhysics Agent PIM (Eric) 01/07 6.PenaltySim Player Agents PIM (Cleyton) 01/07 7.PenaltySimPlayer 2D Animation Agent PIM (Peterson) 01/07 8.PenaltySim GamePhysics Agent Implementation (Eric) 15/07 9.PenaltySim Player Agents Implementation (Cleyton) 15/07 10.PenaltySimPlayer 2D Animation Agent Implementation (Peterson) 15/07

Rollerslam Rollerslam PIM as Instance of KMAPF (Eric, Peterson) 05/08 12.Rollerslam GamePhysics and Referee Agents PIM (Eric) 05/08 13.Rollerslam Player Agents PIM (Cleyton) 05/08 14.Rollerslam 2D Animation Agent PIM (Peterson) 05/08 15.Rollerslam GamePhysics Agent Implementation (Eric) 16.Rollerslam Player Agents Implementation (Eric) 17.Rollerslam 2D Animation Agent Implementation (Peterson)