1. Presentation 1: Planning & Design Software Engineering Team 2 CIS 540, Fall 2001

2. The team  Dave Bacon  Jason Bullok  Justin Hinson  Matt Hoosier  Chris Orosco

3. Description of project A classical strategy game, Hunt the Wumpus, requires a player to navigate through a cave to slay a man-eating beast (the wumpus).

4. Description of project (2) Our task is to design and implement a multiagent version of the game such that: –The agents play the game without help from human operators. –The agents can cooperate to hunt the wumpus more effectively.

5. Introduction: Rules  A cave consists of an n x m grid of cells.

6. Introduction: Rules (2)  Players may walk from one cell to another cell that is directly north, south, east, or west of their location (no diagonal moves).  Some cells contain bottomless pits. Entering such a cell kills the player.

7. Introduction: Rules (3)  The wumpus (immobile) is located in a randomly chosen cell. A player is eaten and dies if he enters the wumpus’s cell.  A pot of gold is located in one cell. A player is awarded bonus points for finding and collecting the gold.

8. Introduction: Rules (4)  The player may kill the wumpus by firing an arrow into the wumpus’s cell when the player occupies an adjacent cell.

9. Introduction: Sensory information  The player begins the game with no knowledge of the cave’s layout or contents.  A player smells a stench if his location is adjacent to the wumpus.  The player feels a breeze if his location is next to a bottomless pit.  The player sees a glitter if the gold is in his current room.

10. Roles PersonTask Dave BaconGUI framework Jason BullokGUI rendering Justin HinsonCore agent implementation Matt HoosierInter-agent cooperation Chris OroscoMain game engine

11. Reporting methods  Code reviews each meeting  Utilize pluggable architecture by demonstrating new functionality at each meeting  Conversations with individual team members

12. Risks  Nobody on team has prior A.I. experience.  Can we successfully re-implement the simulator engine?  Difficulty compartmentalizing the agent implementation – nextMove() algorithm will depend on all state information

13. Risk reduction  Study AI texts. Specific sections of textbooks exist for the “Wumpus World” problem.  Encapsulate the game logic inside abstracted “Agent” interface so that rest of project can proceed while logic is under development.

14. Resource requirements  Hardware –Server for CVS repository. Will be supplied by a team member.  Software –Java 2 development kit  Other –Artificial Intelligence texts

15. Work Breakdown TaskDescriptionDep. ADefine project statement BProduce object modelA CImplement engine skeletonB DDevise inter-agent strategyB EBuild GUI around engineC FImplement logic in agentC GIntegrate agent communication and strategy with core algorithm D, F HIntegration, testingG, E

16. A: Define project stmt. Overall time: 1.5 weeks –Search web for similar projects (3 days) –Determine which set of rules to use for game (1 days) –Determine level of cooperation needed between agents ( 3 days ) –Integrate above results into project statement as given in this presentation. (2 days)

17. B: Produce object model  Overall time: 1 week –Produce UML diagram of existing simulator (2 days) –Determine what abstractions are re-usable (1 day) –Create a model that allows data hiding, encapsulation, and interchangeability (3 days)

18. C: Implement skeleton  Overall time: 1 week –Generate stub interfaces for basic compilation (4 days) –Add ability for top-level engine to iterate through agents’ turns and relay units of communication (4 days)

19. D: Inter-agent protocols  Overall time: 3 weeks –Devise basic algorithm (2 weeks) –Map algorithm onto extension of object model (2 days) –Implement cooperative agents as Agent objects (7 days)

20. E: UI  Overall time: 5 weeks –Define API (interfaces) that allows generic printAgent() functionality (1 week) –Wrap a temporary text interface around the game engine (1 week) –Implement graphical ability to display current “snapshot” of game (2 weeks) –Develop cell-rendering modules that handle delegation of drawing characters (2 weeks) –Add animation to above cell renderers (2 weeks) –Integrate cell-renderers with general GUI framework (1 week)

21. F: “Smart” agent  Total time: 3 weeks –Build a stand-in agent with no intelligence (3 days) –Add ability for agent to determine which squares are safe/unsafe (2 days) –Implement safe route-calculation algorithm (5 days) –Logic for choosing among unsafe squares (3 days) –Find fastest way to kill wumpus once somebody discovers his location (4 days) –Add peer-to-peer passing of basic perception information (4 days)

22. G: Integrating strategy  Total time: 2 weeks –Adapt single-agent game logic with multi- agent strategy algorithm (1 week) –Integration testing on above result (1 weeks)

23. H: Overall testing  Total: 1 week –Combine GUI and simulation engine (2 days) –Test result ( 2 days ) –Write documentation (2 days)

24. Schedule: Gantt chart Project def. O.M. Skeleton Cooperation Graphics Smart agent Integration Testing

25. Schedule: projections  Schedule milestones: –Design finished: Sep. 24 –Skeleton done: Oct. 4 –GUI done: Oct. 22 –Logic done: Nov. 22 –Finish: Nov. 30

26. Design: background  Existing simulator is shown at left.  This engine is useful as a guide, but is not reusable.

27. Design: old game engine diagram

28. Design: old engine problems  Model is entangled, not much abstraction.  Poor encapsulation (public member variables abound)  “Everybody knows about everybody”  Long, complex algorithms with no documentation/comments

29. Design: new object model

30. Designs: benefits of new model  Pluggability: –Programming against interfaces allows swapping modules in/out at will –Allows incremental development of intelligence, inter-agent strategy