Search Algorithms

In order to find the solution in a search space we must traverse and evaluate different possible solutions. There are several strategies depending on the knowledge at hand. A search space is basically a set of all possible solutions.

Blind

When there is no information about the problem we must define a method capable of traversing the search space in a orderly fashion. These include:

  1. Uniform_Cost

  2. Breadth-First

  3. Depth-First

  4. Depth-Limited

  5. Iterative_Deepening

Heuristic

If we can define a method or formula capable of evaluating the current solution (implies knowledge about the problem) we can use that knowledge to our advantage. These algorithms include:

  1. Hill_Climber

  2. A*

  3. SMA*

  4. IDA*

Stochastic

These methods use both well defined steps and a random factor. Other stochastic search methods include evolutionary algorithms.

  1. Random_search

  2. Simulated_Annealing


Related Topics

Features

Methods

Related Material

Papers

  1. Papers/A_Navigation_Graph_for-Real-time_Crowd_Animation_on_Multilayered_and_Uneven_Terrain
  2. Papers/Animating_Reactive_Motion_Using_Momentum-based_Inverse_Kinematics_and_Captured_Motion
  3. Papers/Automated_Extraction_and_Parameterization_of_Motions
  4. Papers/Behavior_Planning_for_Character_Animation
  5. Papers/Case-based_Planning_and_Execution_for_Real-time_Strategy_Games
  6. Papers/Combining_Artificial_Intelligence_Methods:_Automating_the_Playing_of_DEFCON
  7. Papers/Context_based_variation_of_character_animation_by_physical_simulation
  8. Papers/Dynamic_Response_for_Motion_Capture_Animation
  9. Papers/Fast_Planning_Through_Planning_Graph_Analysis
  10. Papers/Fast_and_Accurate_Goal-Directed_Motion_Synthesis_for_Crowds
  11. Papers/Good_Decisions_under_Fire:_Strategic_and_Tactical_AI_in_Real-World_3D_Environments
  12. Papers/Group_Motion_Editing
  13. Papers/Hierarchical_Path_Planning_for_Multi-size_Agents_in_Heterogeneous_Environments
  14. Papers/Hierarchical_Reinforcement_Learning_with_Deictic_Representation_in_a_Computer_Game
  15. Papers/Interactive_Motion_Generation_from_Examples
  16. Papers/Interactive_Navigation_in_Complex_Environments_Using_Path_Planning
  17. Papers/Learning_to_Steer_on_Winding_Tracks_Using_Semi-Parametric_Control_Policies
  18. Papers/Motion_Patches_Building_Blocks_for_Virtual_Environments_Annotated_with_Motion_Data
  19. Papers/Motion_Synthesis_from_Annotations
  20. Papers/POSH_Tools_for_Game_Agent_Development_by_Students_Non-Programmers
  21. Papers/Planning_Biped_Locomotion
  22. Papers/Planning_with_Hierarchical_Task_Networks_in_Video_Games
  23. Papers/Populating_Ancient_Pompeii_with_Crowds_of_Virtual_Romans
  24. Papers/Precomputed_Search_Trees:_Planning_for_Interactive_Goal-Driven_Animation
  25. Papers/Precomputing_Avatar_Behavior_From_Human_Motion_Data
  26. Papers/Real-time_Path_Planning_for_Virtual_Agents_in_Dynamic_Environments
  27. Papers/Simulating_Interactions_of_Avatars_in_High_Dimensional_State_Space
  28. Papers/Synthesizing_Physically_Realistic_Human_Motion_in_Low-Dimensional,_Behavior-Specific_Spaces
  29. Papers/Tactical_Pathfinding_in_Urban_Environments
  30. Papers/Time-sliced_Pathfinding_on_Arbitrary_Polygon_Surfaces
  31. Papers/Towards_a_Game_Agent

Presentations

Methods/Search (last edited 2008-08-17 11:52:59 by GuilhermeRodrigues)