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Jun Tanimoto Last modified date:2021.08.20

Graduate School
Undergraduate School
Administration Post
Director of the Green Asia International Leaders Education Center

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Academic Degree
Country of degree conferring institution (Overseas)
Field of Specialization
Urban Architectural Environment Engineering, Human-Environment-Social System Engineering
Total Priod of education and research career in the foreign country
Outline Activities
The Urban and Architectural Environment Laboratory focuses on solving complex, multidisciplinary problems related to urban and architectural environment, leading to a better future. Our research activities are summarized into following four aspects.

- Observation and modeling of Heat Island phenomenon in urban area
- Modeling of building physics from the viewpoints of thermal and fluid dynamics system
- Developments of passive cooling techniques for urban and architectural space
- Modeling and controlling for prodigious waste flow in urban area
- High performance computer application in the field of urban and architectural environment engineering

And addition to above those, we have started several challenging frontier studies related to Human-Environment-Social System.
Research Interests
  • Modelling on Human-Environment-Social System
    keyword : Human-Environment-Social System, Complex system, Applied mathematics, Evolutionary game theory
  • Development of passive controlling applied to urban-architectural systems
    keyword : Passive design, Development
  • Simultaneous evaluation for energy conservation and environmental amenities applied to architectural environment
    keyword : Heat transfer theory, Hygrothermal transfer theory
  • Study in Urban-Architectural Environment system and Urban climatology
    keyword : Urban-Architectural Environment, Urban climatology, Heat island
Academic Activities
1. Jun Tanimoto , Sociophysics Approach to Epidemics, Springer, 2021.03, [URL], This book presents the fundamentals of evolutionary game theory and applies them to the analysis of epidemics, which is of paramount importance in the aftermath of the worldwide COVID-19 pandemic. The primary objective of this monograph is to deliver a powerful tool to model and analyze the spread of an infectious disease during a pandemic as well as the human decision dynamics. The book employs a variant of the “vaccination game,” in which a mathematical epidemiological model dovetails with evolutionary game theory. From a social physics standpoint, this book introduces an extended concept of the vaccination game starting from the fundamental issues and touching on the newest practical applications.

The book first outlines the fundamental basis of evolutionary game theory, in which a two-player and two-strategy game, the so-called 2 × 2 game, and a multi-player game are concisely introduced, and the important issue of how social dilemmas are quantified is highlighted.

Subsequently, the book discusses various recent applications of the extended concept of the vaccination game so as to quantitatively evaluate provisions other than vaccination, including practical intermediate protective measures such as mask-wearing, efficiency of quarantine compared with that of isolation policies for suppressing epidemics, efficiency of preemptive versus late vaccination, and optimal subsidy policies for vaccination..
2. 谷本潤, Mathematical Analysis of Environmental System, Springer, 2014.02, [URL].
1. 谷本潤, Coevolution of discrete, mixed, and continuous strategy systems boosts in the spatial prisoner's dilemma and chicken games, Applied Mathematics and Computation,, 304, 1, 20-27, 2017.01.
2. 谷本潤, How does resolution of strategy affect network reciprocity in spatial prisoner’s dilemma games?, Applied Mathematics and Computation,, 301, 15, 36-42, 2016.11.
3. Matsuzawa R, 谷本潤, A social dilemma structure in diffusible public goods, EPL,, 116, 38005-38005, 2016.10.
4. Fukuda E, 谷本潤, Iwamura Y, Nakamura K, Akimoto M, Field measurement analysis to validate lane-changing behavior in a cellular automaton model, Physical Review E,, 94, 052209-052209, 2017.08.
5. Iwamura R, 谷本潤, Fukuda E, Effect of intermediate defense measures in voluntary vaccination games, Journal of Statistical Mechanics: Theory and Experiment,, 093501-093501, 2016.09.
6. Matsuzawa Ryou, 谷本潤, Fukuda Eriko, Spatial prisoner's dilemma games with zealous cooperators, Physical Review E,, 94, 022114-022114, 2016.06.
7. 谷本潤, A Enhancement of cooperation in the spatial prisoner's dilemma with a coherence-resonance effect through annealed randomness at a cooperator-defector boundary; comparison of two variant models, Physica A,, 462, 714-724, 2016.05.
8. 谷本潤, A multi-community homogeneous small-world network and its fundamental characteristics, Physica A, 2016.09.
9. 谷本潤, Nakamura,K., Social dilemma structure hidden behind traffic flow with route selection, Physica A,, 459, 92-99, 2016.08.
10. 谷本潤, 萩島 理, 池谷 直樹, Hirose,C., Effect of turbulent flow on wall pressure coefficients of block arrays within urban boundary layer, Building and Environment, 100, 28-39, 2016.03.
11. 谷本潤, 萩島 理, 池谷 直樹, Chung, J., Wind-tunnel study of scalar transfer phenomena for surfaces of block arrays and smooth walls with dry patches, Boundary-Layer Meteorology, 157, 219-236, 2015.11.
12. 谷本潤, Sagara, H., How the indirect reciprocity with co-evolving norm and strategy for 2 × 2 prisoner's dilemma game works for emerging cooperation, Physica A, 438, 595-602, 2016.01.
13. 谷本潤, Fukuda, E., Effects of stubborn decision-makers on vaccination and disease propagation in social networks, International Journal of Automation and Logistics, 2, 78-92, 2016.01.
14. Tanimoto, Jun, Satoshi Kokubo, Zheng Wang, Marco Jusup, Universal scaling for the dilemma strength in evolutionary games, Physics of Life Reviews,, 2015.06, Why would natural selection favor the prevalence of cooperation within the groups of selfish individuals? A fruitful framework to address this question is evolutionary game theory, the essence of which is captured in the so-called social dilemmas. Such dilemmas have sparked the development of a variety of mathematical approaches to assess the conditions under which cooperation evolves. Furthermore, borrowing from statistical physics and network science, the research of the evolutionary game dynamics has been enriched with phenomena such as pattern formation, equilibrium selection, and self-organization. Numerous advances in understanding the evolution of cooperative behavior over the last few decades have recently been distilled into five reciprocity mechanisms: direct reciprocity, indirect reciprocity, kin selection, group selection, and network reciprocity. However, when social viscosity is introduced into a population via any of the reciprocity mechanisms, the existing scaling parameters for the dilemma strength do not yield a unique answer as to how the evolutionary dynamics should unfold. Motivated by this problem, we review the developments that led to the present state of affairs, highlight the accompanying pitfalls, and propose new universal scaling parameters for the dilemma strength. We prove universality by showing that the conditions for an ESS and the expressions for the internal equilibriums in an infinite, well-mixed population subjected to any of the five reciprocity mechanisms depend only on the new scaling parameters. A similar result is shown to hold for the fixation probability of the different strategies in a finite, well-mixed population. Furthermore, by means of numerical simulations, the same scaling parameters are shown to be effective even if the evolution of cooperation is considered on the spatial networks (with the exception of highly heterogeneous setups). We close the discussion by suggesting promising directions for future research including (i) how to handle the dilemma strength in the context of co-evolution and (ii) where to seek opportunities for applying the game theoretical approach with meaningful impact..
15. Tanimoto, Jun, Eriko Fukuda, Mitsuhiro Akimoto, Influence of breaking the symmetry between disease transmission and information propagation networks on stepwise decisions concerning vaccination, Chaos, Solitons & Fractals,, 80, 47-55, 2015.06.
16. Tanimoto, Jun, Shinji Kukida, Aya Hagishima, Naoki Ikegaya, Traffic flow simulation dovetailed with evolutionary game theory, Proc. of 4th International Conference on Simulation and modeling Methodologies, Technologies and Applications, 2014.08.
17. Tanimoto, Jun, The impact of initial cooperation fraction on the evolutionary fate in a spatial prisoner's dilemma game, Applied Mathematics and Computation, 2015.06.
18. Satoshi Kokubo, Zhen Wang, Tanimoto, Jun, Spatial reciprocity for discrete, continuous and mixed strategy setups, Applied Mathematics and Computation ,, 259, 562-568, 2015.05.
19. Tanimoto, Jun, Correlated asynchronous behavior updating with a mixed strategy system in spatial prisoner's dilemma games enhances cooperation, Chaos, Solitons & Fractals,, 80, 39-46, 2015.05.
20. Tanimoto, Jun, Nobuyuki Kishimoto, Network reciprocity created in prisoner’s dilemma games by coupling two mechanisms, Physical Review E,, 91, 042106-042106, 2015.04.
21. Tanimoto, Jun, Network reciprocity created in prisoner’s dilemma games by coupling two mechanisms, Physical Review E , 2015.05.
22. Tanimoto, Jun, Considering individual satisfaction levels enhances cooperation in a spatial prisoner's dilemma game, Chaos, Solitons & Fractals,, 80, 24-30, 2015.04.
23. Tanimoto, Jun, Ogasawara, Takashi, Dynamic noise from action errors enhances network reciprocity in the prisoner’s dilemma game, Journal of Statistical Mechanics: Theory and Experiment,, P1033, 2015.01.
24. Ogasawara, Takashi, Tanimoto, Jun, Fukuda, Eriko, Aya Hagishima, Naoki Ikegaya, Large strategy adaptation neighborhood bolsters network reciprocity in prisoner's dilemma, Proc. of 18th Asia Pacific System on Intelligent and Evolutionary System, CD-ROM, 2014.11.
25. Fukuda, Eriko, Tanimoto, Jun, Impact of stubborn individuals on spread of infectious disease under voluntary vaccination policy, Proc. of 18th Asia Pacific System on Intelligent and Evolutionary System, CD-ROM, 2014.11.
26. Tanimoto, Jun, Ogasawara, Takashi, Fukuda, Eriko, Aya Hagishima, Naoki Ikegaya, Effect of a large gaming neighborhood and a strategy adaptation neighborhood for bolstering network reciprocity in a prisoner's dilemma game, Journal of Statistical Mechanics: Theory and Experiment,, P12024, 2014.12.
27. Tanimoto, Jun, Fujiki, Takuya, Kukida, Shinji, Naoki Ikegaya, Aya Hagishima, Acquisition of the field measurement data relating to lane change actions, International Journal of Modern Physics C,, 26, 1550072-1550072, 2015.04.
28. Tanimoto, Jun, Fujiki, Takuya, Wang, Zhen, Aya Hagishima, Naoki Ikegaya, Dangerous drivers foster social dilemma structures hidden behind a traffic flow with lane changes, Journal of Statistical Mechanics: Theory and Experiment,, P11027, 2014.11.
29. Tanimoto, Jun, Dynamics of spatial traveler’s dilemma games, Journal of Statistical Mechanics: Theory and Experiment,, P11010, 2014.11.
30. Tanimoto, Jun, Impact of deterministic and stochastic updates on network reciprocity in prisoner's dilemma game, Physical Review E,, 90, 022105, 2014.08.
31. Fukuda, Eriko, Kokubo, Satoshi, Tanimoto, Jun, Wang, Zhen, Aya Hagishima, Naoki Ikegaya, Risk assessment for infectious disease and its impact on voluntary vaccination behavior in social networks, Chaos, Solitons & Fractals,, 68, 1-9, 2014.10.
32. Tanimoto, Jun, Kukida, Shinji, Aya Hagishima, Social dilemma structures hidden behind a traffic flow with lane changes, Journal of Statistical Mechanics: Theory and Experiment, 10.1088/1742-5468/2014/07/P07019, P07019, 2014.08.
33. 谷本潤, Kukida Shinji, 池谷直樹, 萩島理, Analytical solutions of Fukui-Ishibashi (FI) model and Quick-Start (QS) model, Journal of Applied Mathematics and Physics,, 2, 7, 691-697, 2014.08.
34. Tanimoto, Jun, Assortative and dissortative priorities for game interaction and strategy adaptation significantly bolster network reciprocity in the prisoner's dilemma, Journal of Statistical Mechanics: Theory and Experiment, doi:10.1088/1742-5468/2014/05/P05003, P05003, 2014.04.
35. Miyaji, Kohei, Tanimoto、Jun, Hagishima, Aya, Ikegaya, Naoki, Influence of stochastic perturbation of both action updating and strategy updating in mixed-strategy 2 times 2 games on evolution of cooperation, Physical Review E,, 88, 062149, 2013.12, [URL].
36. Tanimoto、Jun, Simultaneously selecting appropriate partners for gaming and strategy adaptation to enhance network reciprocity in the prisoner's dilemma, Physical Review E,, 89, 012106, 2014.01, [URL].
37. Wang, Zhen, Kokubo, Satoshi, Tanimoto、Jun, Fukuda, Eriko, Shigaki, Keizo, Insight on the so-called spatial reciprocity, Physical Review E,, 88, 042145, 2013.10, [URL].
38. Tanimoto、Jun, Shigaki, Keizo, Wang, Zhen, Fukuda, Eriko, Effect of initial fraction of cooperators on cooperative behavior in evolutionary prisoner's dilemma, PLOS One,, 8, 11, e76942, 2013.11, [URL].
39. Hagishima, Aya, Tanimoto, Jun, Ikegaya, Naoki, Mitsuyasu, Seijirou, Stochastic characteristics of thermal load in a single dwelling in a residential building based on building energy simulation coupled with a sub-model for considering variation on behavior schedules of residents, Proc. of 13th Building Simulation 2013, 2013.08.
40. Mohamad Mohd Faizal1, Hagishima, Aya, Ikegaya, Naoki, Tanimoto, Jun, Wind-induced natural ventilation in typical single story terraced houses in Malaysia, Proc. of 13th Building Simulation 2013, 2013.08.
41. Kishimoto, Noriyuki, Kokubo, Satoshi, Tanimoto, Jun, Combination of continuous and binary strategies enhances network reciprocity in a spatial prisoner's dilemma game, Chaos, Solitons & Fractals,, 56, 83-90, 2013.11, [URL].
42. Miyaji, Kohei, Wang, Zhen, Tanimoto, Jun, Hagishima, Aya, Ikegaya, Naoki, Direct reciprocity in spatial populations enhances R-reciprocity as well as ST-Reciprocity, PLOS One,, 8, 8, e71961, 2013.08, [URL].
43. Tanimoto, Jun, Difference of reciprocity effect in two coevolutionary models of presumed two-player and multi-player games, Physical Review E,, 87, 6, 062136, 2013.06, [URL].
44. Sato, Tsuyoshi, Hagishima, Aya, Ikegaya, Naoki, Tanimoto, Jun, Particle image velocimetry measurement of unsteady turbulent flow around regularly arranged high-rise building models, International Journal of High-Rise Buildings, 2, 2, 105-113, 2013.06.
45. Miyaji, Kohei, Tanimoto, Jun, Wang, Zhen, Hagishima, Aya, Kokubo, Satoshi, The evolution of fairness in the coevolutionary ultimatum games, Chaos, Solitons & Fractals,, 56, 13-18, 2013.11, [URL].
46. Tanimoto, Jun, Co-evolutionary, coexisting learning and teaching agents model for prisoner's dilemma games enhancing cooperation with assortative heterogeneous networks, Physica A,, 392, 13, 2955-2964, 2013.07.
47. Nik Ibrahim,I., Ikegaya,N., Hagishima,A., Tanimoto,J., A study on the similarity between scalar and momentum roughness lengths based on the scalar concentration measurement, Proc. of 1st Asia Conference of International Building Performance Simulation Association (ASim2012), 2012.11.
48. Kishimoto,N., Kokubo,S., Tanimoto,J., Network reciprocity on spatial prisoner’s dilemma games by continuous-binary strategy, Proc. of 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligent Systems (SCIS-ISIS 2012), 2012.11.
49. Shigaki,K., Tanimoto,J., Wang,Z., Hagishima,A, Ikegaya,N, A new Pairwise Fermi update rule, not referring to randomly selected opponent's payoff but social average payoff of same strategy the opponent has, significantly enhances cooperation in spatial prisoner's dilemma games, Physical Review E,, 86, 031141, 2012.11.
50. Tanimoto,J., Hagishima,A., Iwai,T., Ikegaya,N., Total utility demand prediction for multi-dwelling sites by a bottom-up approach considering variations of inhabitants’ behavior schedules, Journal of Building Performance Simulation, 2012.04.
51. Tanimoto,J., Brede,M., Yamauchi,A., Network reciprocity by coexisting learning and teaching strategies, Physical Review E, 85, 2012.08.
52. Park,M., Hagishima,A., Tanimoto,J., Effect of urban vegetation on outdoor thermal environment filed measurement at a scale model site, Building and Environment, 2012.08.
53. Sheikh,A.Z., Hagishima,A., Tanimoto,J., Experimental study of wind-induced ventilation in urban building of cube arrays with various layouts, Journal of Wind Engineering & Industrial Aerodynamics ,, 103, 31-40, 2012., 2012.01.
54. Ikegaya,N., Hagishima,A., Tanimoto,J., Tanaka,Y., Narita,K. Sheikh Ahmad,Z., Geometric Dependence of the Scalar Transfer Efficiency over Rough Surfaces, Boundary-Layer Metrology , 142 (2),, 2012.01.
55. Zhong,W., Kokubo,S., Tanimoto,J., How is the equilibrium of continuous strategy game different from that of discrete strategy game?, BioSystems ,, 107 (2), 89-94, 2012.01.
56. Shigaki,K., Tanimoto.J., Hagishima,A., A Revised Stochastic Optimal Velocity Model Considering the Velocity Gap with a Preceding Vehicle, Journal of Modern Physics C,, 22 (9), 1005-1014, 2011.10.
57. Tanimoto,J., Hagishima,A, Iwai,T., Ikegaya,N., Total utility demand prediction for multi-dwelling sites considering variation of occupant behavior schedules, Proc. of 12th IBPSA Conference, 2011.11.
58. Zaki,S,A., Hagishima,A., Tanimoto,J., Spatial distribution of pressure drag acting on rectangular block arrays with various layouts, Proc. of 12th IBPSA Conference, 2011.11.
59. Tanimoto,J., Nakata,M., Hagishima,A., Ikegaya,N., Spatially correlated heterogeneous aspirations to enhance network reciprocity, Physica A, 2011.11.
60. Shigaki,K., Tanimoto.A., Hagishima,A., A Revised Stochastic Optimal Velocity Model Considering the Velocity Gap with a Preceding Vehicle, International Journal of Modern Physics C, 2011.09.
61. Tanimoto,J., Influence of strategy adaptation speed on network reciprocity for evolutionary prisoner’s dilemma games, Sociobiology, 58, 2, 315-325, 2011.11.
62. Tanimoto,J., Sagara,H., Social diffusive impact analysis based on evolutionary computations for a novel car navigation system sharing individual information in urban traffic systems, Journal of Navigation, 64, 4, 1-15, 64 (4), 1-15 , 2011, 2011.10.
63. Tanimoto,J., A study of a quadruple co-evolutionary model and its reciprocity phase for various Prisoner’s Dilemma games, International Journal of Modern Physics C, 2011.09.
64. Kukida,S., Tanimoto,J., Hagishima,A., Analysis of the influence of lane changing on traffic-flow dynamics based on the cellular automaton model, International Journal of Modern Physics C, 22, 3, 271-281, 2011.04.
65. Tanimoto,J., Hagishima,A., State Transition Stochastic Model for Predicting Off-to-On Cooling Schedule in Dwellings as Implemented using a Multilayered Artificial Neural Network, Journal of Building Performance Simulation, Journal of Building Performance Simulation, 2011.12, Our previous study (Tanimoto & Hagishima (2005), Energy and Buildings) proposed a set of state transition probabilities for the Markov chain dealing with the on/off cooling schedule in dwellings. The probability of turning on an air conditioner was defined in the form of a sigmoid function by the indoor globe temperature. Obviously, a real stochastic event of shifting from the off to on state is affected by not only indoor thermal quality parameters but also other complex factors such as the presence of family members, time of the day, and whether it is a weekday or holiday. In this paper, we report an alternate model, based on a multilayered artificial neural network (MANN), for predicting the off to on cooling schedule. We gathered field measurement data on family dwellings during the summer of 2008 by deploying hygrothermometers with recording functions to measure the room temperature and the globe and blowout air temperature of the air conditioner. The MANN used has nine nodes in both its input and hidden layers and a single node in its output layer, which implies that the state is either shifting from off to on (1) or not (0). The information provided to the input layer nodes includes the time of the day, whether it is a weekday or holiday, the probability of the presence of inhabitants, and the predicted percentage of dissatisfied people (PPD). PPD, derived from PMV theory, is applied as a representative parameter of the indoor thermal quality, in place of the globe temperature, since it accounts for various influences. The field measurement datasets were divided into two parts: teaching data and data for validation. A model trained by the teaching data was confirmed to reproduce the state transition characteristic of the validation period, which seems complex and is determined by the behavior of various inhabitants. The performance of the model in reproducing this behavior is improved over that of the previous model derived from the Markov chain..
66. Wakiyama,M., Tanimoto,J., Reciprocity phase in various 2×2 games by agents equipped with 2-memory length strategy encouraged by grouping for interaction and adaptation, BioSystems,, 103, 93-104, 2010.10.
67. Kokubo,S., Tanimoto,J., Hagishima,A., A new Cellular Automata Model including a decelerating damping effect to reproduce Kerner’s three-phase theory, Phyisica A,, 390, 4, 561-568, 2010.10.
68. Zaki,S,A., Hagishima,A., Tanimoto,J., Ikegaya,N., Aerodynamic parameters of urban building arrays with random geometries, Boundary-Layer Meteorology,, 138 , 1, 99-12, 2010.11.
69. Yamauchi,A., Tanimoto,J., Hagishima,A., An analysis of network reciprocity in Prisoner’s Dilemma games using Full Factorial Designs of Experiment, BioSystems,, 103, 85-92, 2010.10.
70. Tanimoto,J., Hagishima,A., Tanaka,Y., Study of bottleneck effect at an emergency evacuation exit using cellular automata model, Physica A ,, 389 , 24, 5611-5618, 2010.08.
71. Nakata,M., Yamauchi,A., Tanimoto,J., Hagishima,A., Dilemma game structure hidden in traffic flow at a bottleneck due to a 2 into 1 lane junction, Physica A,, 389, 5353-5361, 2010.08.
72. Yamauchi,A, Tanimoto,J., Hagishima,A., What controls network reciprocity in the prisoner’s dilemma game?, BioSystems,, 102 , 2-3, 82-87, 2010.06.
73. Tanimoto,J., Editorial; Evolutionary World; Games, Complex networks, Agent simulations, International Journal of Bio-inspired Computation , 3, 3, 2011.09.
74. Tanimoto,J., Effect of assortativity by degree on emerging cooperation in a 2 x 2 dilemma game played on an evolutionary network, Physica A,, 2010.04, [URL].
75. , [URL].
76. Tanimoto,J., Hagishima,A, Total Utility Demand Prediction System for dwellings based on stochastic processes of actual inhabitants, Journal of Building Performance Simulation, 2010.04.
77. Jun Tanimoto, Atsuo Yamauchi, Game participation cost brakes the advantage of heterogeneous networks for evolving cooperation, Proc. of 13th Asia-Pacific Workshop on Intelligent Evolutionary Systems, 2009.12.
78. Atsuo Yamauchi, Jun Tanimoto, Aya Hagishima, Factorial analysis on network reciprocity in Prisoner’s Dilemma Game, Proc. of 13th Asia-Pacific Workshop on Intelligent Evolutionary Systems, 2009.12.
79. Makoto Nakata, Atsuo Yamauchi, Jun Tanimoto, Aya Hagishima, Dilemma game structure in traffic flow brought by a bottleneck, Proc. of 13th Asia-Pacific Workshop on Intelligent Evolutionary Systems, 2009.12.
80. Tanimoto,J., Hagishima,A;, Total utility demand prediction based on probabilistically generated behavioral schedules of actual inhabitants, 11th IBPSA Conference, 2009.08.
81. Aya Hagishima1 , Jun Tanimoto1, Koji Nagayama1 and Sho Meno1, Aerodynamic Parameters of Regular Arrays of Rectangular Blocks with Various Geometries, Boundary-Layer Meteorology, 132 , 315-337 , 2009., 2009.09.
82. Oliveira,J.T., Hagishima, A., Tanimoto,J., Estimation of passive cooling efficiency for environmental design in Brazil,, Energy and Buildings , 41, 809-813, 2009., 2009.07.
83. Yamauchi,A., Tanimoto,J., Hagishima,A. Sagara,H., Dilemma Game Structure Observed in Traffic Flow at a 2-to-1 Lane Junction, Physical Review E, 79 , #036104, 2009.05.
84. Tanimoto,J., Promotion of cooperation through co-evolution of networks and strategy in a 2 x 2 game, Physica A, 2009.03.
85. Tanimoto,J., A simple scaling of the effectiveness of supporting mutual cooperation in donor-recipient games by various reciprocity mechanisms, BioSystems, 2009.03.
86. Tanimoto,J., Co-evolution Model of Networks and Strategy in a 2 × 2 Game Emerges Cooperation, IEEE World Congress on Computational Intelligence, 117-122, 2008.06.
87. Hagishima, A., Tanimoto J., Wind tunnel experiment in drag force coefficient of urban-like roughness with height variation, Proc of AWAS 2008, 2008.06.
88. Tanimoto, J., Emergence of cooperation in patchy habitat with mortality and colonization based on various 2 x 2 games, Sociobiology , 52 (2), 185-206, 2008.05.
89. Hagishima. A., Narita. K., Tanimoto. J., Field experiment on transpiration from isolated urban plants, Hydrological Process , 21, 1217-1222, 2007.11, [URL].
90. Tanimoto, J., What initially brought about communications?, BioSystems, 92 (1) , 82-90, 2008.06, [URL].
91. Tanimoto,J., Hagishima,A., Sagara,H., Validation of Methodology for Utility Demand Prediction Considering Actual Variations in Inhabitant Behavior Schedules, Journal of Building Performance Simulation, 1 (1), 2008.04.
92. Sagara,H., Tanimoto,J., Analysis of Impact of Communication Among Different Norms in Norm Reputation Model, Proc. of 11th Asia-Pacific Workshop on Intelligent Evolutionary Systems, 2007.11.
93. Tanimoto,J., Promotion of cooperation by payoff noise in a 2 × 2 game, Physical Review E , 76, #041130, 2007.11, [URL].
94. Tanimoto,J., Dilemma-solving effects by the coevolution of both networks and strategy in a 2 x 2 game, Physical Review E, 2007.12.
95. Sagara,H., Tanimoto,J., A Study on Social Diffusive Impacts of a Novel Car-Navigation-System Sharing Individual Information in Urban Traffic Systems, IEEE Congress on Evolutionary Computation 2007, 2007.09.
96. Tanimoto,J., Emergence of Cooperation Supported by Communication in a One-Shot 2 x 2 Game, IEEE Congress on Evolutionary Computation 2007, 2007.09.
97. Tanimoto,J., Hagishima,A., Sagara,H., Validation of the Probabilistic Methodology to Generate Actual Inhabitants’ Behavior Schedules for Accurate Prediction of Maximum Energy Requirement, 10th IBPSA Conference, 2007.09.
98. (10) Jun Tanimoto, A study of indirect reciprocity involving a reputation system or a simple tag system in a one-shot, multi-player game, BioSystems, in Press, [URL].
99. Jun Tanimoto, Does a Tag System Effectively Support Emerging Cooperation?, Journal of Theoretical Biology, 247(4), 756-764, 2007.09, [URL].
100. Jun Tanimoto, A study on emergence of Coordinated Alternating Reciprocity in a 2x2 game with 2-memory length strategy, BioSystems, 2007.09, [URL].
101. Jun Tanimoto, Aya Hagishima, Hiroki Sagara, Validation of Probabilistic Methodology for Generating Actual Inhabitants' Behavior Schedules for Accurate Prediction of Maximum Energy Requirements, Energy and buildings, 43, 610-619, 2007.09, [URL].
102. Jun Tanimoto, Aya Hagishima, Hiroki Sagara, A methodology for peak energy requirement considering actual variation of occupants’ behavior schedules, Building and Environment, 43 (4), 610-619, 2007.09, [URL].
103. Jun Tanimoto, Differences in Dynamics between Discrete Strategies and Continuous Strategies in a Multi-player Game with a Linear Payoff Structure, BioSystems, 90(2), 568-572, 2007.10, [URL].
104. Jun Tanimoto, Hiroki Sagara, Relationship between dilemma occurrence and the existence of a weakly dominant strategy in a two-player symmetric game, BioSystems, 90(1), 105-114, 2007.06, [URL].
105. Jun Tanimoto, Haruyuki Fujii, A model for Collusive tendering based on a multiagent approach, Agent-Based Modering Meets Gameing Simulation, Springer-Verlag, 2005, pp.89-100, 2005.12.
106. Jun Tanimoto, Aya Hagishima, Cooling Load Simulation Considering Actual Variation of Inhabitants’ Behavior for Accurate Estimation of Urban Maximum Energy Requirement, 9th IBPSA Conference (Building Simulation 2005), 2005.12.
107. Hagishima. A.; Tanimoto.J.; Narita.K, Intercomparisons of experimental research on convective heat transfer coefficient of urban surfaces, Boundary-Layer Meteorology, 10.1007/s10546-005-2078-7, 117, 3, 551-576, 117, 551-576, 2005.01.
108. Jun Tanimoto and Aya Hagishima, State transition probability forthe Markov Model dealing with on/off cooling schedule in dwellings, Energy and Buildings, 10.1016/j.enbuild.2004.02.002, 37, 3, 181-187, Vol.37 No.3,pp.181-187, 2005.03.
109. Jun Tanimoto, Environmental dilemma game to establish a sustainable society dealing with an emergent value system, Physica D, 10.1016/j.physd.2004.09.016, 200, 1-2, 1-24, Vol. 200, pp.1-24, 2005.01.
Works, Software and Database
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Membership in Academic Society
  • The Japan Society of Hydrology and Water Resources
  • The Japan Society for Industrial and Applied Mathematics
  • Society of Heating
  • International Building Performance Simulation Association
  • Information Processing Society of Japan
  • Architectural Instituteof Japan
  • Air-ConditioningandSanitary Engineers of Japan
  • Architectual Institute of Japan
  • Society of Heating, Air-Conditioning and Sanitary Engineers of Japan
  • Information Processing Society of Japan
  • Japan Society of Hydrology & Water Resources
  • Japan Society for Industrial and Applied Mathematics
  • Japanese Society for Artificial Intelligence
  • International Building Performance Simulation Association Japan
  • International Building Performance Simulation Association
  • The effect of assortative mixing on emerging cooperation in an evolutionary network game
  • 学外
  • 学外
  • 学外
  • 学外
Educational Activities
For graduate students, two classes are provided at Department of Environment Energy Engineering. For under graduates, 7 classes including experiments and exercises are provided at Department of Energy Science and Engineering.
Professional and Outreach Activities
I have been dedicating as;
Committee member at Ministry of Foreign Affairs/ MJIIT – Japan University Consortium,
Deputy chair at Energy science field at JICA/ SEED-Net.

I have also been active as Editor at many first-notch international journals such as PLOS One, Applied Mathematics & Computation and so forth.

I am responsible as Editor-in-Chief at EVERGREEN, which is an open access journal for interdisciplinary studies. I have dedicated to boost up the visibility of EVERGREEN and its citation statistics such as Cite Score and other indexes. Now EVERGREE has establish worldwide good-reputation, which does help to boost up School reputation as well as entire KU.