An auto-adaptive dead reckoning algorithm for distributed interactive simulation
PADS '99 Proceedings of the thirteenth workshop on Parallel and distributed simulation
Networked virtual environments: design and implementation
Networked virtual environments: design and implementation
Future Generation Computer Systems
Parallel and Distribution Simulation Systems
Parallel and Distribution Simulation Systems
On the suitability of dead reckoning schemes for games
NetGames '02 Proceedings of the 1st workshop on Network and system support for games
Accuracy in dead-reckoning based distributed multi-player games
Proceedings of 3rd ACM SIGCOMM workshop on Network and system support for games
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Offloading AI for peer-to-peer games with dead reckoning
IPTPS'09 Proceedings of the 8th international conference on Peer-to-peer systems
ARIVU: power-aware middleware for multiplayer mobile games
Proceedings of the 9th Annual Workshop on Network and Systems Support for Games
The near-term feasibility of P2P MMOG's
Proceedings of the 9th Annual Workshop on Network and Systems Support for Games
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In games, the goals and interests of players are key factors in their behavior. However, techniques used by networked games to cope with infrequent updates and message loss, such as dead reckoning, estimate a player's movements based on previous observations only. The estimations are typically done using dynamics of motion, taking only inertia and external factors (e.g., gravity, wind) into account while completely ignoring the player's goals (e.g., chasing other players or collecting objects). This paper proposes AntReckoning: a dead reckoning algorithm, inspired from ant colonies, which models the players' interests to predict their movements. AntReckoning incorporates a player's interest in specific locations, objects, and avatars in the equations of motion in the form of attraction forces. In practice, these points of interest generate pheromones, which fade and spread in the game world, and are a source of attraction. Our simulations using mobility traces from World of Warcraft and Quake III show that AntReckoning improves the accuracy by up to 30% over traditional dead reckoning techniques.