Increasing Replayability with Deliberative and Reactive Planning

Opponent behavior in today's computer games is often the result of a static set of Artificial Intelligence (AI) behaviors or a fixed AI script. While this ensures that the behavior is reasonably intelligent, it also results in very predictable behavior. This can have an impact on the replayabil...

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Bibliographische Detailangaben
Hauptverfasser:	Lent, Michael van, Riedl, Mark O, Carpenter, Paul, McAlinden, Ryan, Brobst, Paul
Format:	Report
Sprache:	eng
Schlagworte:	ADAPTIVE OPPONENT ARCHITECTURE ADAPTIVE SYSTEMS ARTIFICIAL INTELLIGENCE BEHAVIOR COGNITION COGNITIVE SKILLS COMBAT SIMULATION COMPUTER GAMES Computer Programming and Software COMPUTER PROGRAMS Cybernetics DELIBERATIVE PLANNING DPOCL(DECOMPOSITIONAL PARTIAL ORDER CAUSAL LINK) FSC(FULL SPECTRUM COMMAND) GAME THEORY Military Operations, Strategy and Tactics MILITARY PLANNING MILITARY STRATEGY MILITARY TRAINING MISSIONS NOVEL STRATEGIES OPPONENT BEHAVIOR REACTION(PSYCHOLOGY) REACTIVE PLANNING REAL TIME REPLAYABILITY SKILLS SOAR COMPUTER PROGRAM SOFTWARE ARCHITECTURE STRATEGIC ARTIFICIAL INTELLIGENCE STRATEGIC WARFARE TACTICAL ARTIFICIAL INTELLIGENCE TACTICAL WARFARE UNPREDICTABILITY WAR GAMES
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Beschreibung
Zusammenfassung:	Opponent behavior in today's computer games is often the result of a static set of Artificial Intelligence (AI) behaviors or a fixed AI script. While this ensures that the behavior is reasonably intelligent, it also results in very predictable behavior. This can have an impact on the replayability of entertainment-based games and the educational value of training-based games. This paper proposes a move away from static, scripted AI by using a combination of deliberative and reactive planning. The deliberative planning (or Strategic AI) system creates a novel strategy for the AI opponent before each gaming session. The reactive planning (or Tactical AI) system executes this strategy in real-time and adapts to the player and the environment. These two systems, in conjunction with a future automated director module, form the Adaptive Opponent Architecture. This paper describes the architecture and the details of the deliberative and reactive planning components. The original document contains color images.