Department of Mathematics
City, University of London
Northampton Square
London EC1V 0HB
I will be teaching three lecture
courses this year:
Game Theory EPM951
Mathematical Processes for Finance
MA3614
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. More recently 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.
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. Revisiting the “fallacy of averages” in ecology:
Expected gain per unit time equals expected gain divided by expected time.
Accepted by the Journal of Theoretical Biology.
127. Erovenko,I.E., Bauer,J., Broom,M. Pattni,K & Rychtar,J. The effect of network topology on optimal
exploration strategies and the evolution of cooperation in a mobile population.
Accepted by Proceedings of the Royal Society of London A.
128. Broom,M., Erovenko,I.V., Rowell,J.T. & Rychtar,J.
Models and measures of animal aggregation and dispersal. Accepted by the
Journal of Theoretical Biology.
129. Bauer,J., Broom,M. & Alonso,
E. The Stabilisation of Equilibria in Evolutionary Game Dynamics through
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