The Experts below are selected from a list of 300 Experts worldwide ranked by ideXlab platform
Haruhiro Katayose - One of the best experts on this subject based on the ideXlab platform.
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evaluating human like behaviors of video game agents autonomously acquired with Biological Constraints
Advances in Computer Entertainment Technology, 2013Co-Authors: Nobuto Fujii, Yuichi Sato, Hironori Wakama, Koji Kazai, Haruhiro KatayoseAbstract:Designing the behavioral patterns of video game agents (Non-player character: NPC) is a crucial aspect in developing video games. While various systems that have aimed at automatically acquiring behavioral patterns have been proposed and some have successfully obtained stronger patterns than human players, those patterns have looked mechanical. When human players play video games together with NPCs as their opponents/supporters, NPCs' behavioral patterns have not only to be strong but also to be human-like. We propose the autonomous acquisition of NPCs' behaviors, which emulate the behaviors of human players. Instead of implementing straightforward heuristics, the behaviors are acquired using techniques of reinforcement learning with Q-Learning and pathfinding through an A* algorithm, where Biological Constraints are imposed. Human-like behaviors that imply human cognitive processes were obtained by imposing sensory error, perceptual and motion delay, physical fatigue, and balancing between repetition and novelty as the Biological Constraints in computational simulations using "Infinite Mario Bros.". We evaluated human-like behavioral patterns through subjective assessments, and discuss the possibility of implementing the proposed system.
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Advances in Computer Entertainment - Evaluating Human-like Behaviors of Video-Game Agents Autonomously Acquired with Biological Constraints
Lecture Notes in Computer Science, 2013Co-Authors: Nobuto Fujii, Yuichi Sato, Hironori Wakama, Koji Kazai, Haruhiro KatayoseAbstract:Designing the behavioral patterns of video game agents (Non-player character: NPC) is a crucial aspect in developing video games. While various systems that have aimed at automatically acquiring behavioral patterns have been proposed and some have successfully obtained stronger patterns than human players, those patterns have looked mechanical. When human players play video games together with NPCs as their opponents/supporters, NPCs' behavioral patterns have not only to be strong but also to be human-like. We propose the autonomous acquisition of NPCs' behaviors, which emulate the behaviors of human players. Instead of implementing straightforward heuristics, the behaviors are acquired using techniques of reinforcement learning with Q-Learning and pathfinding through an A* algorithm, where Biological Constraints are imposed. Human-like behaviors that imply human cognitive processes were obtained by imposing sensory error, perceptual and motion delay, physical fatigue, and balancing between repetition and novelty as the Biological Constraints in computational simulations using "Infinite Mario Bros.". We evaluated human-like behavioral patterns through subjective assessments, and discuss the possibility of implementing the proposed system.
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Advances in Computer Entertainment - Autonomously acquiring a video game agent's behavior: letting players feel like playing with a human player
Lecture Notes in Computer Science, 2012Co-Authors: Nobuto Fujii, Yuichi Sato, Hironori Wakama, Haruhiro KatayoseAbstract:Designing behavior patterns of video game agents (COM players) is a crucial aspect of video game development. While various systems aiming to automatically acquire behavior patterns has been proposed and some have successfully obtained stronger patterns than human players, the obtained behavior patterns looks mechanical. We present herein an autonomous acquisition of video game agent behavior, which emulates the behavior of a human player. Instead of implementing straightforward heuristics, the behavior is acquired using Q-learning, a reinforcement learning, where, Biological Constraints are imposed. In the experiments using Infinite Mario Bros., we observe that behaviors that imply human behaviors are obtained by imposing sensory error, perceptual and motion delay, and fatigue as Biological Constraints.
Gabriel G. Katul - One of the best experts on this subject based on the ideXlab platform.
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Biological Constraints on water transport in the soil–plant–atmosphere system
Advances in Water Resources, 2013Co-Authors: Stefano Manzoni, Giulia Vico, Amilcare Porporato, Gabriel G. KatulAbstract:An effective description of water transport in the soil–plant–atmosphere continuum (SPAC) is needed for wide-ranging applications in hydrology and climate-vegetation interactions. In this contribution, the theory of water movement within the SPAC is reviewed with emphasis on the eco-physiological and evolutionary Constraints to water transport. The description of the SPAC can be framed at two widely separated time scales: (i) sub-hourly to growing season scales, relevant for hydro-climatic effects on ecosystem fluxes (given a set of plant hydraulic traits), and (ii) inter-annual to centennial scales during which either hydraulic traits may change, as individuals grow and acclimate, or species composition may change. At the shorter time scales, water transport can be described by water balance equations where fluxes depend on the hydraulic features of the different compartments, encoded in the form of conductances that nonlinearly depend on water availability. Over longer time scales, ontogeny, acclimation, and shifts in species composition in response to environmental changes can impose Constraints on these equations in the form of tradeoffs and coordinated changes in the hydraulic (and biochemical) parameters. Quantification of this evolutionary coordination and the related tradeoffs offers novel theoretical tactics to constrain hydrologic and biogeochemical models.
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Biological Constraints on water transport in the soil plant atmosphere system
Advances in Water Resources, 2013Co-Authors: Stefano Manzoni, Giulia Vico, Amilcare Porporato, Gabriel G. KatulAbstract:An effective description of water transport in the soil–plant–atmosphere continuum (SPAC) is needed for wide-ranging applications in hydrology and climate-vegetation interactions. In this contribution, the theory of water movement within the SPAC is reviewed with emphasis on the eco-physiological and evolutionary Constraints to water transport. The description of the SPAC can be framed at two widely separated time scales: (i) sub-hourly to growing season scales, relevant for hydro-climatic effects on ecosystem fluxes (given a set of plant hydraulic traits), and (ii) inter-annual to centennial scales during which either hydraulic traits may change, as individuals grow and acclimate, or species composition may change. At the shorter time scales, water transport can be described by water balance equations where fluxes depend on the hydraulic features of the different compartments, encoded in the form of conductances that nonlinearly depend on water availability. Over longer time scales, ontogeny, acclimation, and shifts in species composition in response to environmental changes can impose Constraints on these equations in the form of tradeoffs and coordinated changes in the hydraulic (and biochemical) parameters. Quantification of this evolutionary coordination and the related tradeoffs offers novel theoretical tactics to constrain hydrologic and biogeochemical models.
Nobuto Fujii - One of the best experts on this subject based on the ideXlab platform.
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evaluating human like behaviors of video game agents autonomously acquired with Biological Constraints
Advances in Computer Entertainment Technology, 2013Co-Authors: Nobuto Fujii, Yuichi Sato, Hironori Wakama, Koji Kazai, Haruhiro KatayoseAbstract:Designing the behavioral patterns of video game agents (Non-player character: NPC) is a crucial aspect in developing video games. While various systems that have aimed at automatically acquiring behavioral patterns have been proposed and some have successfully obtained stronger patterns than human players, those patterns have looked mechanical. When human players play video games together with NPCs as their opponents/supporters, NPCs' behavioral patterns have not only to be strong but also to be human-like. We propose the autonomous acquisition of NPCs' behaviors, which emulate the behaviors of human players. Instead of implementing straightforward heuristics, the behaviors are acquired using techniques of reinforcement learning with Q-Learning and pathfinding through an A* algorithm, where Biological Constraints are imposed. Human-like behaviors that imply human cognitive processes were obtained by imposing sensory error, perceptual and motion delay, physical fatigue, and balancing between repetition and novelty as the Biological Constraints in computational simulations using "Infinite Mario Bros.". We evaluated human-like behavioral patterns through subjective assessments, and discuss the possibility of implementing the proposed system.
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Advances in Computer Entertainment - Evaluating Human-like Behaviors of Video-Game Agents Autonomously Acquired with Biological Constraints
Lecture Notes in Computer Science, 2013Co-Authors: Nobuto Fujii, Yuichi Sato, Hironori Wakama, Koji Kazai, Haruhiro KatayoseAbstract:Designing the behavioral patterns of video game agents (Non-player character: NPC) is a crucial aspect in developing video games. While various systems that have aimed at automatically acquiring behavioral patterns have been proposed and some have successfully obtained stronger patterns than human players, those patterns have looked mechanical. When human players play video games together with NPCs as their opponents/supporters, NPCs' behavioral patterns have not only to be strong but also to be human-like. We propose the autonomous acquisition of NPCs' behaviors, which emulate the behaviors of human players. Instead of implementing straightforward heuristics, the behaviors are acquired using techniques of reinforcement learning with Q-Learning and pathfinding through an A* algorithm, where Biological Constraints are imposed. Human-like behaviors that imply human cognitive processes were obtained by imposing sensory error, perceptual and motion delay, physical fatigue, and balancing between repetition and novelty as the Biological Constraints in computational simulations using "Infinite Mario Bros.". We evaluated human-like behavioral patterns through subjective assessments, and discuss the possibility of implementing the proposed system.
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Advances in Computer Entertainment - Autonomously acquiring a video game agent's behavior: letting players feel like playing with a human player
Lecture Notes in Computer Science, 2012Co-Authors: Nobuto Fujii, Yuichi Sato, Hironori Wakama, Haruhiro KatayoseAbstract:Designing behavior patterns of video game agents (COM players) is a crucial aspect of video game development. While various systems aiming to automatically acquire behavior patterns has been proposed and some have successfully obtained stronger patterns than human players, the obtained behavior patterns looks mechanical. We present herein an autonomous acquisition of video game agent behavior, which emulates the behavior of a human player. Instead of implementing straightforward heuristics, the behavior is acquired using Q-learning, a reinforcement learning, where, Biological Constraints are imposed. In the experiments using Infinite Mario Bros., we observe that behaviors that imply human behaviors are obtained by imposing sensory error, perceptual and motion delay, and fatigue as Biological Constraints.
Stefano Manzoni - One of the best experts on this subject based on the ideXlab platform.
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Biological Constraints on water transport in the soil–plant–atmosphere system
Advances in Water Resources, 2013Co-Authors: Stefano Manzoni, Giulia Vico, Amilcare Porporato, Gabriel G. KatulAbstract:An effective description of water transport in the soil–plant–atmosphere continuum (SPAC) is needed for wide-ranging applications in hydrology and climate-vegetation interactions. In this contribution, the theory of water movement within the SPAC is reviewed with emphasis on the eco-physiological and evolutionary Constraints to water transport. The description of the SPAC can be framed at two widely separated time scales: (i) sub-hourly to growing season scales, relevant for hydro-climatic effects on ecosystem fluxes (given a set of plant hydraulic traits), and (ii) inter-annual to centennial scales during which either hydraulic traits may change, as individuals grow and acclimate, or species composition may change. At the shorter time scales, water transport can be described by water balance equations where fluxes depend on the hydraulic features of the different compartments, encoded in the form of conductances that nonlinearly depend on water availability. Over longer time scales, ontogeny, acclimation, and shifts in species composition in response to environmental changes can impose Constraints on these equations in the form of tradeoffs and coordinated changes in the hydraulic (and biochemical) parameters. Quantification of this evolutionary coordination and the related tradeoffs offers novel theoretical tactics to constrain hydrologic and biogeochemical models.
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Biological Constraints on water transport in the soil plant atmosphere system
Advances in Water Resources, 2013Co-Authors: Stefano Manzoni, Giulia Vico, Amilcare Porporato, Gabriel G. KatulAbstract:An effective description of water transport in the soil–plant–atmosphere continuum (SPAC) is needed for wide-ranging applications in hydrology and climate-vegetation interactions. In this contribution, the theory of water movement within the SPAC is reviewed with emphasis on the eco-physiological and evolutionary Constraints to water transport. The description of the SPAC can be framed at two widely separated time scales: (i) sub-hourly to growing season scales, relevant for hydro-climatic effects on ecosystem fluxes (given a set of plant hydraulic traits), and (ii) inter-annual to centennial scales during which either hydraulic traits may change, as individuals grow and acclimate, or species composition may change. At the shorter time scales, water transport can be described by water balance equations where fluxes depend on the hydraulic features of the different compartments, encoded in the form of conductances that nonlinearly depend on water availability. Over longer time scales, ontogeny, acclimation, and shifts in species composition in response to environmental changes can impose Constraints on these equations in the form of tradeoffs and coordinated changes in the hydraulic (and biochemical) parameters. Quantification of this evolutionary coordination and the related tradeoffs offers novel theoretical tactics to constrain hydrologic and biogeochemical models.
Yuichi Sato - One of the best experts on this subject based on the ideXlab platform.
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evaluating human like behaviors of video game agents autonomously acquired with Biological Constraints
Advances in Computer Entertainment Technology, 2013Co-Authors: Nobuto Fujii, Yuichi Sato, Hironori Wakama, Koji Kazai, Haruhiro KatayoseAbstract:Designing the behavioral patterns of video game agents (Non-player character: NPC) is a crucial aspect in developing video games. While various systems that have aimed at automatically acquiring behavioral patterns have been proposed and some have successfully obtained stronger patterns than human players, those patterns have looked mechanical. When human players play video games together with NPCs as their opponents/supporters, NPCs' behavioral patterns have not only to be strong but also to be human-like. We propose the autonomous acquisition of NPCs' behaviors, which emulate the behaviors of human players. Instead of implementing straightforward heuristics, the behaviors are acquired using techniques of reinforcement learning with Q-Learning and pathfinding through an A* algorithm, where Biological Constraints are imposed. Human-like behaviors that imply human cognitive processes were obtained by imposing sensory error, perceptual and motion delay, physical fatigue, and balancing between repetition and novelty as the Biological Constraints in computational simulations using "Infinite Mario Bros.". We evaluated human-like behavioral patterns through subjective assessments, and discuss the possibility of implementing the proposed system.
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Advances in Computer Entertainment - Evaluating Human-like Behaviors of Video-Game Agents Autonomously Acquired with Biological Constraints
Lecture Notes in Computer Science, 2013Co-Authors: Nobuto Fujii, Yuichi Sato, Hironori Wakama, Koji Kazai, Haruhiro KatayoseAbstract:Designing the behavioral patterns of video game agents (Non-player character: NPC) is a crucial aspect in developing video games. While various systems that have aimed at automatically acquiring behavioral patterns have been proposed and some have successfully obtained stronger patterns than human players, those patterns have looked mechanical. When human players play video games together with NPCs as their opponents/supporters, NPCs' behavioral patterns have not only to be strong but also to be human-like. We propose the autonomous acquisition of NPCs' behaviors, which emulate the behaviors of human players. Instead of implementing straightforward heuristics, the behaviors are acquired using techniques of reinforcement learning with Q-Learning and pathfinding through an A* algorithm, where Biological Constraints are imposed. Human-like behaviors that imply human cognitive processes were obtained by imposing sensory error, perceptual and motion delay, physical fatigue, and balancing between repetition and novelty as the Biological Constraints in computational simulations using "Infinite Mario Bros.". We evaluated human-like behavioral patterns through subjective assessments, and discuss the possibility of implementing the proposed system.
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Advances in Computer Entertainment - Autonomously acquiring a video game agent's behavior: letting players feel like playing with a human player
Lecture Notes in Computer Science, 2012Co-Authors: Nobuto Fujii, Yuichi Sato, Hironori Wakama, Haruhiro KatayoseAbstract:Designing behavior patterns of video game agents (COM players) is a crucial aspect of video game development. While various systems aiming to automatically acquire behavior patterns has been proposed and some have successfully obtained stronger patterns than human players, the obtained behavior patterns looks mechanical. We present herein an autonomous acquisition of video game agent behavior, which emulates the behavior of a human player. Instead of implementing straightforward heuristics, the behavior is acquired using Q-learning, a reinforcement learning, where, Biological Constraints are imposed. In the experiments using Infinite Mario Bros., we observe that behaviors that imply human behaviors are obtained by imposing sensory error, perceptual and motion delay, and fatigue as Biological Constraints.