Team Member AI in an FPS and Goal Oriented Action Planning

1. Team Member AI in an FPS and Goal Oriented Action Planning

2. Overview • Correct Positioning • Correct Movement • Correct Behavior • Supporting the Player • Implementation • GOAP • AIISC

3. Correct Positioning • Should not be in the players line of sight • Should not be in the players line of fire • Should be visible to the player • Should give player first opportunity to act • Positioning depends on body stance • Should move out of sight if possible

4. Correct Positioning Continued

5. Correct Movement • Find smallest angle to a clear view • Move away from the players current viewing direction • Proximity • Level of awareness and readiness to fire • Should use tactical strategies • Respect current context of the situation • Move at same speed as player

6. Movement Continued

7. Movement Continued

8. Correct Behavior • Use cover if available • Selective firing • Reloading

9. Supporting the Player • Capture the flag • Support player in every movement • Reporting • In face of danger • Taking orders • Protecting the player

10. Player is the Most Important • Complement game play • Use similar weapons • Get choice of items after the player

11. Implementation of Squad Tactics • Implementation Hierarchy • 1: Player • 2: Threat • 3: Environmental • 4: Team Manager

12. Implementation Continued • Finding an Available NPC • O = # of enemies within range • Availability = (1+N)(1+O)(1+P)+(Q∞) • N = # of enemies in covering area • P = # of enemies threatening team • Q = Supporting team member (T/F) • Fire Staggering • Should not target same enemy • Team manager should change cover area

13. GOAP(Goal Oriented Action Planning) • A decision making architecture that allows characters to decide not only what to do, but how to do it. • Not a commonly used technique in today’s games • Superior to more common techniques such as Finite State Machines (FSM) and Rule-based Systems (RBS).(AIISC)

14. Why GOAP • Less repetitive than a FSM • Less predictable than FSM • Can adapt action to fit current situation • A better way to simulate intelligence

15. Definitions • Goal: any condition that an agent wants to satisfy • Agent can have many goals A Initial state Goals C B A B C

16. Definitions • Goal… • Only one goal active at any one time

17. Sussman Anomaly www.csee.umbc.edu/471/lectures

18. Definitions • Goal • Three categories of gaming goals • Relaxed • Investigative • Aggressive

19. Definitions Cont • Goals are not hard coded and do not contain a plan • Plan: a sequence of actions that takes an agent from a starting state to a state that satisfies a goal • Action: a single step within a plan that make an agent do something • Actions have effect(s) and may have precondition(s)

20. Benefits of GOAP • Characters can find alternate solutions to problems • Characters can handle dependencies that may not have been thought of at development time • Difficult to manage every possible situation • Characters do not have to use all possible actions (creates different behaviors)

21. Implementing GOAP • Planner Search • World Representation • Planner Optimization

22. Implementation Continued

23. Implementation Continued

24. AIISC • AI Interface Standards Committee • Their benefits • Modularity • Workflow • Gameplay • Would like to define an API that is appealing to game developers • Determine how real-time dynamic planning can be used in practice

25. References • AI Game Programming Wisdom 2 • AI Game Programming Wisdom • The 2004 AIISC Report • Symbolic Representation of Game World State: Toward Real-Time Planning in Games