Department of Mathematics
City, University of London
Northampton Square
London EC1V 0HB
I will be teaching the following
lecture course this year:
Optimization and Decision Making
EPM945
My main research interest is the application of game theory
to the mathematical modelling of biology, especially using the concept of the
Evolutionarily Stable Strategy (ESS). My work has generally been theoretical,
considering both purely mathematical work on the theory of games in an
evolutionary context and more specific problems when a particular animal
behaviour or trait is concerned. I have published and continue to publish work
in the three main areas listed below.
Mathematical models of evolution
This area involves the development of the general mathematical theory of
evolution, rather than any specific application. Early work considered Patterns
of Evolutionarily Stable Strategies; a theoretical investigation into the
coexistence of different ESSs in the important game class matrix games. A key
theme has been multi-player game theory. Most evolutionary game theory concerns
two-player games only; this work includes an extension of the theory to many
players. A second important theme has been the modelling of evolution on graphs,
where populations can possess a complex non-homogeneous structure. These two area have been brought together in a new framework
for more evolution on structured populations, which I have developed with Jan
Rychtar from the University of North Carolina at Greensboro, which is a central
area of my current research.
Models of parasitism
I have modelled two major types of parasitic behaviour on birds. The first of
these involves the modelling of kleptoparasitism,
where animals acquire food by stealing from others. This work began with the
development of a general modelling framework for kleptoparasitism
and considers the circumstances under which it is best to steal food (or not)
for different scenarios and varying biological and mathematical assumptions. The
second area is the modelling of brood parasitism. Raising young can be costly,
and some birds lay their eggs in the nests of other birds to avoid this cost.
Various models of both conspecific and interspecific parasitism are considered.
I am continuing to work on kleptoparasitism in
particular.
Evolutionary responses to predators and group living
A key priority for many animals is the avoidance of predators. Many such prey
animals choose to live in groups, and these two features are often strongly
related. I have considered two major types of interactions between prey and
predators, the first of these being antipredator vigilance in animal groups.
This an extension of a well-established theory involving trade-offs in time
spent watching for predators and foraging, into dynamic changes in group
structure and in spatial and positioning factors. The second is the
co-evolution of defence and signalling. Many animals possess high levels of
toxins to make them unpalatable to potential predators. Such defences are
invisible, so they are often also brightly coloured to signal these defences,
and success depends upon a sufficient number of
conspecifics with these traits for predators to learn to avoid them.
I would be interested in supervising research students in
any of the general areas described above. For more details on my research, look
at some of the publications from the list below.
Book
Broom,M.
& Rychtar,J. (2013). Game-Theoretical Models
in Biology. Chapman and Hall.
The second edition of this book will
appear in August 2022.
Papers
1. Broom,M.,
Cannings,C. & Vickers,G.T.
(1993) On the number of local maxima of a constrained quadratic form.
Proceedings of the Royal Society of London A 443 573-584.
2. Broom,M.,
Cannings,C. & Vickers,G.T.
(1994) Sequential methods for generating patterns of ESS's. Journal of
Mathematical Biology 32 597-615.
3. Broom,M., Cannings,C. & Vickers,G.T. (1996) Patterns of ESS's. Adding pairs to
an ESS. Mathematical Biosciences 136 21-34.
4. Broom,M.,
Cannings,C. & Vickers,G.T.
(1996) Choosing a Nest Site: Contests and Catalysts. American Naturalist 147
1108-1114.
5. Broom,M.,
Cannings,C. & Vickers,G.T.
(1996) Some examples of multi-player game dynamics. Proceedings of the European
Mathematical Genetics Meeting, Padova University Press 105-114.
6. Broom,M.,
Cannings,C. & Vickers,G.T.
(1997) Multi-player matrix games. Bulletin of Mathematical Biology 59
931-952.
7. Broom,M. Cannings,C. & Vickers,G.T. (1997) A sequential-arrivals model of
territory acquisition. Journal of Theoretical Biology 189 257-272.
8. Broom,M. & Ruxton,G.D. (1998)
Evolutionarily Stable Stealing: Game Theory applied to Kleptoparasitism.
Behavioral Ecology 9 397-403.
9. Broom,M. & Ruxton,G.D. (1998)
Modelling responses in vigilance rates to arrivals to and departures from a
group of foragers. IMA Journal of Mathematics Applied in Medicine and Biology
15 387-400.
10. Broom,M. & Ruxton,G.D. (1999) A game
theoretic model of kleptoparasitism. Proceedings of BioMedSim 99 27-31.
11. Ruxton,G.D. & Broom,M. (1999) Evolution
of kleptoparasitism as a war of attrition. Journal of
Evolutionary Biology 12 755-759.
12. Proctor,C.J.
& Broom,M. (2000) A spatial model of
antipredator vigilance. IMA Journal of Mathematics Applied in Medicine and
Biology 17 75-93.
13. Broom,M., Cannings,C. & Vickers,G.T. (2000) Evolution in Knockout Contests: the
Fixed Strategy Case. Bulletin of Mathematical Biology 62 451-466.
14. Broom,M.
(2000) Patterns of ESSs: the Maximal Pattern Conjecture revisited. Journal
of Mathematical Biology 40 406-412.
15. Broom,M.
(2000) Bounds on the number of ESSs of a matrix game. Mathematical Biosciences
167 163-175.
16. Broom,M., Cannings,C., & Vickers,G.T. (2000) Evolution in Knockout Contests: the
Variable Strategy Case. Selection 1 5-21.
17. Broom,M., Cannings,C. & Vickers,G.T. (2000) A sequential-arrivals model of
territory acquisition II. Journal of Theoretical Biology 207 389-403.
18. Ruxton,G.D., Broom,M. & Colegrave,N. (2001) Are unusually coloured eggs a
signal to potential conspecific brood parasites? American Naturalist 157
451-458.
19. Broom,M. & Ruxton,G.D. (2001)
A model of dominance and resource division amongst a group of animals of
differing quality. Population Ecology 43 213-220.
20. Proctor,C.J., Broom,M. & Ruxton,G.D. (2001) Modelling antipredator vigilance and
flight response in group foragers when warning signals are ambiguous. Journal
of Theoretical Biology 211 409-417.
21. Broom,M.
& Ruxton,G.D. (2002) A Game Theoretic Approach
to Conspecific Brood Parasitism. Behavioral Ecology
13 321-327.
22. Broom,M. (2002) Using game theory to model the
evolution of information: an illustrative game. Entropy 4 35-46.
23. Ward,A.J.W.,Hoare,D.J.,Couzin,I.D.,Broom,M. & Krause,J. (2002) The
effects of parasitism and body length on positioning within wild fish shoals
Journal of Animal Ecology 71 10-14.
24. Broom,M.
(2002) A unified model of dominance hierarchy formation and maintenance.
Journal of Theoretical Biology 219 63-72.
25. Broom,M.
& Cannings,C. (2002) Modelling dominance
hierarchy formation as a multi-player game. Journal of Theoretical Biology 219
397-413.
26. Ruxton,G.D. & Broom,M. (2002)
Intraspecific brood parasitism can increase the number of eggs an
individual lays in its own nest. Proceedings of the Royal Society of London B
269 1989-1992.
27. Ward,A.J.W., Botham,M.S., Hoare,D.J., James,R., Broom,M., Godin,J.G.J. & Krause,J. (2002) Association patterns and shoal
fidelity in the three-spined stickleback. Proceedings of the Royal Society of
London B 269 2451-2455.
28. Proctor,C.J., Broom,M. & Ruxton,G.D. (2003) A communication-based spatial model
of antipredator vigilance. Journal of Theoretical Biology 220 123-137.
29. Broom,M & Ruxton,G.D.
(2003) Evolutionarily stable kleptoparasitism:
consequences of different prey types. Behavioral
Ecology 14 23-33.
30. Broom,M.
(2003) The use of multiplayer game theory in the modeling
of biological populations. Comments on Theoretical Biology 8 103-123.
31. Broom,M., Tang,Q. & Waxman,D. (2003) Mathematical Analysis of a Model
describing Evolution of an Asexual Population in a Changing Environment.
Mathematical Biosciences 186 93-108.
32. Broom,M., Borries,C. & Koenig,A. (2004) Infanticide and infant defense by males- modeling the
conditions in primate multi-male groups. Journal of Theoretical Biology 231
261-270.
33. Luther,R.M.
& Broom,M. (2004) Rapid convergence to an
equilibrium state in kleptoparasitic populations.
Journal of Mathematical Biology 48 325-339.
34. Broom,M.
& Ruxton,G.D. (2004) A framework for
modelling and analysing conspecific brood parasitism. Journal of Mathematical
Biology 48 529-544.
35. Broom,M., Luther,R.M. & Ruxton,G.D. (2004) Resistance is useless? - extensions
to the game theory of kleptoparasitism. Bulletin of
Mathematical Biology 66 1645-1658.
36. Broom,M. & Ruxton,G.D. (2005)
You can run or you can hide: optimal strategies for cryptic prey against
pursuit predators. Behavioral Ecology 16 534-540.
37. Broom,M.
(2005) Evolutionary games with variable payoffs. Comptes
Rendus Biologies 328
403-412.
38. Broom,M.,
Speed,M.P. & Ruxton,G.D.
(2005) Evolutionarily stable investment in secondary defences. Functional
Ecology 19 836-843.
39. Ruxton,G.D., Fraser, C. & Broom,M.
(2005) An evolutionarily stable joining policy for group foragers. Behavioral Ecology 16 856-864.
40. Yates,G.E.
& Broom,M. (2005) A stochastic model of the
distribution of unequal competitors between resource patches. Journal of
Theoretical Biology 237 227-237.
41. Speed,M.P., Ruxton,G.D. & Broom,M. (2006) Automimicry and the evolution of
discrete prey defences. Biological Journal of the Linnean Society 87 393-402.
42. Proctor,C.J., Broom,M. & Ruxton,G.D. (2006) Antipredator vigilance in birds:
modelling the `edge' effect. Mathematical Biosciences 199 79-96.
43. Broom,M., Speed,M.P. & Ruxton,G.D. (2006) Evolutionarily stable defence and
signalling of that defence. Journal of Theoretical Biology 242 32-43.
44. Jackson,A.L.,Beauchamp,G.,Broom,M. & Ruxton,G.D. (2006)
Evolution of anti-predator traits in response to a flexible targeting
strategy by predators. Proceedings of the Royal Society of London B 273
1055-1062.
45. Fraser,C.P.,Ruxton,G.D. & Broom,M. (2006)
Public information and patch estimation for group foragers: a re-evaluation
of patch quitting strategies in a patchy environment. Oikos 112 311-321.
46. Broom,M.
& Rychtar,J. (2007) The evolution of a kleptoparasitic system under adaptive dynamics. Journal of
Mathematical Biology 54 151-177.
47. Ellis,J.,Broom,M. & Jones,S. (2007) Protein-RNA
interactions: Structural analysis and functional classes of Protein-RNA binding
sites. Proteins: structure, function and bioinformatics 66 903-911.
48. Broom,M.,Ruxton,G.D. & Speed,M.P.
(2007) Evolutionarily Stable Investment in Anti-predatory Defences and
Aposematic Signalling. In: Mathematical Modeling of
Biological Systems, Volume II. A. Deutsch, R. Bravo de la Parra, R. de Boer, O.
Diekmann, P. Jagers, E. Kisdi, M. Kretzschmar, P. Lansky and H. Metz (eds). Birkhauser, Boston, 37-48.
49. Luther,R.M.,
Broom,M. & Ruxton,G.D.
(2007) Is food worth fighting for? ESS's in mixed populations of
kleptoparasites and foragers. Bulletin of Mathematical Biology 69 1121-1146.
50. Broom,M.,Nouvellet,P.,Bacon,J.P. & Waxman,D. (2007)
Parameter-free testing of the shape of a probability distribution.
Biosystems 90 509-515.
51. Yates,G.E.
& Broom,M. (2007) A stochastic model of kleptoparasitism. Journal of Theoretical Biology 248
480-489.
52. Ruxton,G.D., Speed, M.P. & Broom,M.
(2007) The importance of initial protection of conspicuous mutants for the
coevolution of defense and aposematic signaling of the defense: A modeling study. Evolution 61 2165-2174.
53. Langridge,K.V.,
Broom,M. & Osorio, D. (2007) Selective
signalling by cuttlefish to predators. Current Biology 17 R1044-R1045.
54. Broom,M., Ruxton,G.D. & Kilner,R.M. (2008) Host life history strategies and the
evolution of chick-killing by brood parasitic offspring. Behavioral
Ecology 19 22-34.
55. Broom,M. & Rychtar,J. (2008) An
analysis of the fixation probability of a mutant on special classes of
non-directed graphs. Proc. Roy. Soc. London A 464 2609-2627.
56. Broom,M., Rychtar,J. & Sykes,C. (2008) The Evolution of Kleptoparasitism
under Adaptive Dynamics Without Restriction. Journal of Interdisciplinary
Mathematics 11 479-494.
57. Broom,M., Luther,R.M., Ruxton,G.D. & Rychtar,J.
(2008) A game-theoretic model of kleptoparasitic behavior in polymorphic populations. Journal of Theoretical
Biology 255 81-91.
58. Harrison,M.D.
& Broom, M. (2009) A game-theoretic model of interspecific brood
parasitism with sequential decisions. Journal of Theoretical Biology 256
504-517.
59. Broom,M. Rychtar,J. & Stadler,B.
(2009) Evolutionary Dynamics on Small-Order Graphs. Journal of
Interdisciplinary Mathematics 12 129-140.
60. Broom,M.,
Luther,R.M. & Rychtar,J.
(2009) A Hawk-Dove game in kleptoparasitic
populations. Journal of Combinatorics, Information and System Science 4
449-462.
61. Broom,M.
& Rychtar,J. (2009) A game theoretical model
of kleptoparasitism with incomplete information.
Journal of Mathematical Biology 59 631-649.
62. Broom,M., Koenig,A. & Borries,C. (2009) Variation in dominance hierarchies
among group-living animals: modeling stability and
the likelihood of coalitions. Behavioral Ecology 20
844-855.
63. Kiss, I. Z., Broom, M., and Rafols, I. (2009) Can epidemic models describe
the diffusion of research topics across disciplines? In Birger Larsen and
Jacqueline Leta (Eds.) Proceedings of the 12th International Conference of the
International Society for Scientometrics and Informetrics, Rio de Janeiro.
64. Ruxton,G.D., Speed,M.P. & Broom,M. (2009) Identifying the ecological conditions
that select for intermediate levels of aposematic signalling. Evolutionary
Ecology 23 491-501.
65. Broom,M.
(2009) Balancing risks and rewards: the logic of violence. Frontiers in
Neuroscience Vol.3.
66. Kiss, I.Z.,
Broom, M., Craze, P. & Rafols, I. (2010) Can epidemic models describe the
diffusion of topics across disciplines?. Journal of Informetrics
4 74-82.
67. Broom,M., Crowe.M, Fitzgerald.M & Rychtar,J.
(2010) The stochastic modelling of kleptoparasitism
using a Markov process. Journal of Theoretical Biology 264 266-272.
68. Broom,M., Hadjichrysanthou,C.
& Rychtar,J. (2010) Evolutionary games on
graphs and the speed of the evolutionary process. Proceedings of the Royal
Society A 466 1327-1346.
69. Broom,M., Higginson,A.D. & Ruxton,G.D. (2010) Optimal investment across different
aspects of anti-predator defences. Journal of Theoretical Biology 263 579-586.
70. Broom,M., Hadjichrysanthou,C., Rychtar,J. and Stadler,B. (2010) Two
results on evolutionary processes on general non-directed graphs. Proceedings
of the Royal Society A 466 2795-2798.
71. Broom,M. & Rychtar,J. (2011) Kleptoparasitic melees - modelling food stealing featuring
contests with multiple individuals. Bulletin of Mathematical Biology 73 683-699.
72. Broom,M. & Ruxton,G.D. (2011)
Some mistakes go unpunished - the evolution of all or nothing signalling.
Evolution 65 2743-2749.
73. Hadjichrysanthou,C., Broom,M.
& Rychtar,J. (2011) Evolutionary games on
star graphs under various updating rules. Dynamic Games and Applications 1
386-407.
74. Broom,M., Rychtar,J. & Stadler,B. (2011) Evolutionary dynamics on graphs - the
effect of graph structure and initial placement on mutant spread. Journal of
Statistical Theory and Practice 5 369-381.
75. Broom,M & Voelkl,
B. (2012) Two Measures of Effective Population Size for Graphs. Evolution
66 1613-1623.
76. Barker,H.A., Broom,M. & Rychtar,J. (2012) A game theoretical model of kleptoparasitism with strategic arrivals and departures of
beetles at dung pats Journal of Theoretical Biology 300 292-298.
77. Broom,M. & Rychtar,J. (2012) A
general framework for analysing multiplayer games in networks using territorial
interactions as a case study. Journal of Theoretical Biology 302 70-80.
78. Hadjichrysanthou,C. & Broom,M. (2012) When
should animals share? Game theory applied to kleptoparasitic
populations with food sharing. Behavioral Ecology 23
977-991.
79. Broom,M., Hughes,R.N., Burrows,M. & Ruxton,G.D.
(2012) Evolutionarily stable sexual allocation by both stressed and
unstressed potentially simultaneous hermaphrodites within the same population.
Journal of Theoretical Biology 309 96-102.
80. Hadjichrysanthou,C., Broom,M.
& Kiss,I.Z. (2012) Approximating evolutionary
dynamics on networks using a neighbourhood configuration model. Journal of
Theoretical Biology 312 13-21.
81. Broom,M. & Ruxton,G.D. (2012)
Perceptual advertisement by the prey of stalking or ambush predators.
Journal of Theoretical Biology 315 9-16.
82. Argasinski,K. & Broom,M.
(2013) Ecological theatre and the evolutionary game: how environmental and
demographic factors determine payoffs in evolutionary games. Journal of
Mathematical Biology.
83. Broom,M.
& Ruxton,G.D. (2013) On the evolutionary
stability of zero-cost pooled-equilibrium signals. Journal of Theoretical
Biology 323 69-75.
84. Broom,M. (2013) Interactions between searching
predators and hidden prey in Search Theory: A Game Theoretic Perspective Alpern
S., Fokkink R., Gasieniec
L., Lindelauf R., Subrahmanian
V.S. (eds) Springer.
85. Broom,M.
& Cannings,C. (2013) Evolution of a network
with strategic link formation governed by individual preferences. Journal of
Theoretical Biology 335 160-168.
86. Argasinski,K. & Broom,M.
(2013) The nest site lottery: how selectively neutral density dependent
growth suppression induces frequency dependent selection. Theoretical
Population Biology 90 82-90.
87. Broom,M., Rychtar,J. & Sykes,D.G. (2013) The effect of information on payoffs
in kleptoparasitic interactions. Springer Proceedings
in Mathematics and Statistics 64 125-134.
88. Broom,M.,
Ruxton,G.D. & Schaefer,H.M.
(2013) Signal verification can promote reliable signalling. Proceedings of
the Royal Society B 280 20131560.
89. Bruni,M.,
Broom,M. & Rychtar,J.
(2014) Analysing territorial models on graphs. Involve 7 129-149.
90. Teichmann,J., Broom, M. & Alonso, E. (2014) The
application of temporal difference learning in optimal diet models. Journal of
Theoretical Biology 340 11-16.
91. Teichmann,J., Broom,M. &
Alonso, E. (2014) The evolutionary dynamics of aposematism: a numerical
analysis of co-evolution in finite populations. Mathematical Modelling of
Natural Phenomena 9 148-164.
92. Broom,M., Rychtar,J. & Sykes,D.G. (2014) Kleptoparasitic
interactions under asymmetric resource valuation. Mathematical Modelling of
Natural Phenomena 9 138-147.
93. Broom,M.
& Rychtar,J. (2014) Asymmetric games in
monomorphic and polymorphic populations. Dynamic Games and Applications 4
391-406.
94. Broom,M.
& Cannings,C. (2015) Graphic deviation.
Discrete Mathematics 338 701-711.
95. Broom,M, Johanis,M. & Rychtar,J. (2015) The effect of fight cost structure on
fighting behaviour. Journal of Mathematical Biology 71 979-996.
96. Kura,K, Broom,M. & Kandler,A. (2015) Modelling dominance hierarchies under
winner and loser effects. Bulletin of Mathematical Biology 77 927-952.
97. Broom,M, Lafaye,C., Pattni,K. & Rychtar,J. (2015)
A study of the dynamics of multi-player games on small networks using
territorial interactions. Journal of Mathematical Biology 71 1551-1574.
98. Teichmann, J., Alonso, E. & Broom, M. (2015) A
reward-driven model of Darwinian fitness, Proceedings of the 7th International
Joint Conference on Computational Intelligence (IJCCI 2015) - Volume 1: ECTA,
pp. 174-179, Lisbon, Portugal, Scitepress.
99. Pattni,K., Broom,M., Rychtar,J. & Silvers,A.J.
(2015) Evolutionary graph theory revisited: when is an evolutionary process
equivalent to the Moran process?. Proceedings of the Royal Society A 471
2015.0334.
100. Broom,M.
& Rychtar,J. (2016) A model of food stealing
with asymmetric information. Ecological Complexity 26 137-142.
101. Broom,M., Rychtar, J. & Spears-Gill,T.
(2016) The game-theoretical model of using insecticide-treated bed-nets to
fight malaria. Applied Mathematics 7 852-860.
102. Raza,M.S.
& Broom,M. (2016) Survival analysis modelling
with hidden censoring. Journal of Statistical Theory and Practice 10 1-14.
103. Li,A., Broom,M., Du.J. & Wang,L. (2016) Evolutionary
dynamics of general group interactions in structured populations. Physical
Review E 93 022407.
104. Broom,M. & Rychtar,J. (2016) Nonlinear
and Mulitplayer Evolutionary Games in Advances in
Dynamic and Evolutionary Games, Thuijsman,F., Wagener,F. (eds) Birkhauser.
105. Kura,K., Broom,M. & Kandler,A. (2016) A game-theoretical winner and loser
model of dominance hierarchy formation. Bulletin of Mathematical Biology 78
1259-90.
106. Broom,M. & Rychtar,J. (2016) Ideal
cost-free distributions in structured populations for general payoff functions.
Dynamic Games and Applications doi:10.1007/s13235-016-0204-4.
107. Broom,M. & Rychtar,J. (2017) Evolutionary
games with sequential decisions and dollar auctions. Dynamic Games and
Applications doi: 10.1007/s13235-016-0212-4.
108. Chawsheen,T. & Broom,M.
(2017) Seasonal Time-Series Modelling and Forecasting Monthly Mean
Temperature for Decision Making in the Kurdistan Region of Iraq. Journal of
Statistical Theory and Practice 11 604-633.
109. Argasinski,K.
& Broom,M. (2017) Evolutionary stability
under limited population growth. Eco-evolutionary feedbacks and replicator
dynamics. Ecological Complexity doi:10.1016/j.ecocom.2017.04.002.
110. Hadjichrysanthou,C.,
Broom,M. & Rychtar,J.
(2017) Models of kleptoparasitism on networks:
the effect of population structure on food stealing behaviour Journal of
Mathematical Biology doi 10.1007/s00285-017-1177-7.
111. Broom,M. & Cannings,C. (2017) Game theoretical modelling of a
dynamically evolving network I: general target sequences. Journal of Dynamics
and Games
112. Pattni,K., Broom,M. & Rychtar,J. (2017) Evolutionary dynamics and the evolution
of multiplayer cooperation in a subdivided population. Journal of Theoretical
Biology 429 105-115.
113. Teichmann,J., Alonso,E. & Broom, M. (2017)
Reinforcement learning is an effective strategy to create phenotypic variation
and a potential mechanism for the initial evolution of learning. Proceedings of
the Conference on Artificial Evolution 2017.
114. Teichmann,J., Alonso,E. & Broom, M.
(2017) Reinforcement Learning as a model of aposematism. Proceedings of the
Conference on Artificial Evolution 2017.
115. Broom,M,
Johanis,M. & Rychtar,J.
(2018) The effect of fight cost structure on fighting behaviour involving
simultaneous decisions and variable investment levels. Journal of Mathematical
Biology 76 457-482.
116. Spencer,R. & Broom,M. (2018)
A game-theoretical model of kleptoparasitic behaviour
in an urban gull (Laridae) population. Behavioral
Ecology 29 60-78.
117. Broom,M., Collins,D., Vu,T.H.
& Thomas,P. (2018) The Four Regions in
Settlement Space: A Game-Theoretical Approach to Investment Treaty Arbitration.
Part I: Modelling. Law, Probability and Risk 17 55-78.
118. Broom,M., Collins,D., Vu,T.H.
& Thomas,P. (2018) The Four Regions in Settlement
Space: A Game-Theoretical Approach to Investment Treaty Arbitration. Part II:
Cases. Law, Probability and Risk 17 79-98.
119. Broom,M. & Krivan,V. (2018)
Biology and Evolutionary Games: in Tamer Basar,
Georges Zaccour, eds. Handbook of Dynamic Game Theory. Springer.
120. Argasinski,K. & Broom,M. (2018) Interaction rates, vital rates,
background fitness and replicator dynamics: how to embed evolutionary game
structure into realistic population dynamics. Theory in Biosciences 137 33-50.
121. Pattni,K., Broom,M. & Rychtar,J (2018)
Evolving multiplayer networks: modelling the evolution of cooperation in a
mobile population. Discrete and Continuous Dynamical Systems B 23 1975-2004.
122. Broom, M., Pattni, K. & Rychtar, J.
(2018) Generalized Social Dilemmas: The Evolution of Cooperation in
Populations with Variable Group Size. Bulletin of
Mathematical Biology. doi:10.1007/s11538-018-00545-1.
123. Schimit, P.H.T., Pattni, K. &
Broom, M. (2019) Dynamics of multiplayer games on complex networks using
territorial interactions. Physical Review E, 99(3).
doi:10.1103/physreve.99.032306.
124. Overton, C.E., Broom, M.,
Hadjichrysanthou, C. & Sharkey, K.J. (2019) Methods for approximating
stochastic evolutionary dynamics on graphs. Journal of Theoretical Biology, 468
45-59.
125. Wang, L., Ruxton, G.D., Cornell,
S.J., Speed, M.P. & Broom, M. (2019) A theory for investment across
defences triggered at different stages of a predator-prey encounter. Journal of
Theoretical Biology 473 9-19.
126. Broom,M.,
Cressman,R., & Krivan,V.
(2019) Revisiting the `fallacy of averages’ in ecology: Expected gain per
unit time equals expected gain divided by expected time. Journal of Theoretical
Biology483 article 109993.
127. Erovenko,I.E.,
Bauer,J., Broom,M. Pattni,K & Rychtar,J. (2019)
The effect of network topology on optimal exploration strategies and the
evolution of cooperation in a mobile population. Proceedings of the Royal
Society of London A 475 20190399.
128. Bauer,J.,
Broom,M. & Alonso, E. (2019) The
Stabilisation of Equilibria in Evolutionary Game Dynamics through Mutation:
Mutation Limits in Evolutionary Games. Proceedings of the Royal Society of
London A 475 20190355.
129. Broom,M.,
Erovenko,I.V., Rowell,J.T.
& Rychtar,J. (2020) Models and measures of
animal aggregation and dispersal. Journal of Theoretical Biology 494 110002.
130. Cannings,C. & Broom,M.
(2020) Game theoretical modelling of a
dynamically evolving network II: target sequences of score 1. Journal of
Dynamics and Games 7 37-64.
131. Varga,T.,
Garay,J., Rychtar,J. & Broom,M. (2020) A temporal model of territorial defence
with antagonistic interactions. theoretical Population Biology 135 15-35.
132. Bishop,D.T., Broom,M. & Southwell, R. (2020) Chris Cannings: A
Life in Games. Dynamic Games and Applications 10 591-617.
133. Garay,J.,
Cressman,R., Xu,F., Broom,M., Csiszar & V., Mori,
T. (2020) When optimal foragers meet in a game theoretical conflict: A
model of kleptoparasitism. Journal of Theoretical
Biology 502 110306.
134. Broom,M. & Krivan,V. (2020) Two-strategy games with time
constraints on regular graphs. Journal of Theoretical Biology 506,110426.
135. Broom,M., Erovenko,I. & Rychtar,J. (2021)
Modelling evolution in structured populations involving multiplayer
interactions. Dynamic Games and Applications 11 270-293.
136. Sun.S,
Broom,M.,
Johanis,M & Rychtar,J
(2021) A mathematical model of kin selection in floral displays. Journal of
Theoretical Biology 509,110470.
137. Argasiski,K & Broom,M.
(2021) Towards a replicator dynamics model of age structured populations.
Journal of Mathematical Biology 82 44.
138. Aizouk,R. & Broom,M. (2022) Modelling conflicting individual
preference: target sequences and graph realization. Discrete and Continuous
Dynamical Systems Series B, doi:
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139. Scaramangas,A. & Broom,M. (2022) Aposematic signalling in prey-predator
systems: determining evolutionarily stability when prey populations consist of
a single species. Journal of Mathematical Biology 85(2) 13.