ALGORITHMS FOR STEERING SOFTBOTS IN GAME WORLDS Pros Can be
searched using A heuristic search Commonly used paths can be stored
for quick access Cons Worst-case complexity is exponential in
nature Paths may look unrealistic and require post-processing in
some cases 1.GRID-BASED METHODS 2.NAVIGATION MESHES 3.REACTIVE
METHODS 4.AGENT-BASED APPROACHES 5.HYBRID APPROACHES 6.HARDCODED
SYSTEMS 9/24/09VITALE1
Slide 2
ALGORITHMS FOR STEERING SOFTBOTS IN GAME WORLDS Pros Partitions
the environments terrain into polygons Waypoints are used to
connect points that create paths Cons Works best with static
environments Similar issues to Grid-Based Methods 1.GRID-BASED
METHODS 2.NAVIGATION MESHES 3.REACTIVE METHODS 4.AGENT-BASED
APPROACHES 5.HYBRID APPROACHES 6.HARDCODED SYSTEMS
9/24/09VITALE2
Slide 3
ALGORITHMS FOR STEERING SOFTBOTS IN GAME WORLDS Pros Apply
local environmental information to generate movement Characters are
react from intrinsic information within the landscape Reactions are
determined on a per-application basis, most often using potential
fields Cons Bots often get stuck from poorly designed potential
fields 1.GRID-BASED METHODS 2.NAVIGATION MESHES 3.REACTIVE METHODS
4.AGENT-BASED APPROACHES 5.HYBRID APPROACHES 6.HARDCODED SYSTEMS
9/24/09VITALE3
Slide 4
ALGORITHMS FOR STEERING SOFTBOTS IN GAME WORLDS Pros Used often
in computer graphics Behavior is determined by: a specified set of
rules social forces particle swarm methods Cons Requires
quantifying, identifying and controlling abstract knowledge and
information 1.GRID-BASED METHODS 2.NAVIGATION MESHES 3.REACTIVE
METHODS 4.AGENT-BASED APPROACHES 5.HYBRID APPROACHES 6.HARDCODED
SYSTEMS 9/24/09VITALE4
Slide 5
ALGORITHMS FOR STEERING SOFTBOTS IN GAME WORLDS Pros Combines
several approaches in one Can consider local and global information
Cons Difficult to design and implement Requires in-depth knowledge
of the problem 1.GRID-BASED METHODS 2.NAVIGATION MESHES 3.REACTIVE
METHODS 4.AGENT-BASED APPROACHES 5.HYBRID APPROACHES 6.HARDCODED
SYSTEMS 9/24/09VITALE5
Slide 6
ALGORITHMS FOR STEERING SOFTBOTS IN GAME WORLDS Pros Always
engineered with the optimal path solution Direct-control of agent
steering Cons Very restrictive Unresponsive to the smallest change
Non-autonomous 1.GRID-BASED METHODS 2.NAVIGATION MESHES 3.REACTIVE
METHODS 4.AGENT-BASED APPROACHES 5.HYBRID APPROACHES 6.HARDCODED
SYSTEMS 9/24/09VITALE6
Slide 7
PATH PLANNING IN GAMES WITH CA Reynolds & Kinnaird-Heether
[2008] WCCI 2008 Competition; Socially motivated, agent-based
approach: Cultural Algorithms 3D racing environment Parameterizes
rules for an single racecar driver RESULTS: Steers a car around a
track 9/24/09VITALE7
Slide 8
EXAMPLE OF CA OPTIMIZATION Reynolds & Kinnaird-Heether
Applied CA to learn racing parameters Came in second at the WCCI
2008 How can this approach be be scaled up? 9/24/09VITALE8
acceleration(speedX, maxSpeed) if(speedX