PUBLICATIONS

The following is a selective list. For more robotics-related publications please visit the Projects page. For an exhaustive list please visit James’ Google Scholar or ORCID pages.

2024

1. Marshall, J A R, Reina, A (2024) 'On aims and methods of collective animal behaviour', Animal Behaviour 210, 189-197.

2023

1. MaBouDi, H,  Marshall, J A R, Dearden, N (2023) 'How foraging honeybees make fast and accurate decisions'. eLife 12:e86176.

2. Reina, A, Bose, T, Srivastava, V and Marshall, J A R (2023) 'Asynchrony rescues statistically-optimal group decisions from information cascades through emergent leaders'. Royal Society Open Science 10 (3).

3. MaBouDi, H, Roper, M, Guiraud, M, Chittka, L, Marshall, J A R (2023) A neuromorphic model of active vision shows spatio-temporal encoding in lobula neurons can aid pattern recognition in bees. bioRxiv.

2022

1. Marshall, J A R, Reina, A, Hay, C, Dussutour, A, Pirrone, A (2022) 'Magnitude-sensitive reaction times reveal non-linear time costs in multi-alternative decision-making'. PLoS Computational Biology 18(10): e1010523.

2. de Croon, G C H E, Dupeyroux, J J G, Fuller, S B and Marshall, J A R (2022) 'Insect-inspired AI for autonomous robots'. Science Robotics, 7 (67).

3. Reina, A and Marshall J A R (2022) 'Negative feedback may suppress variation to improve collective foraging performance', PLoS Computational Biology 18 (5), e1010090.

2021

1. Pirrone, A, Reina, A, Stafford, T, Marshall, J A R and Gobet, F (2022) ‘Magnitude-sensitivity: rethinking decision-making’, Trends in Cognitive Sciences 26, pp. 66-80.

2. Chandrasekhar, A, Marshall, J A R, Austin, C, Navlakha, S and Gordon, D M (2021) ‘Better tired than lost: turtle ant trail networks favour coherence over short edges’, PLoS Computational Biology 17 (10), e1009523.

3. Talamali, M S, Saha, A, Marshall, J A R, Reina, A (2021) ‘When less is more: robot swarms adapt better to changes with constrained communication’, Science Robotics, 6(56): eabf1416.

   • ‘Robot swarms communicate best when messages spread neighbor to neighbor’, PNAS Journal Club.

4. MaBouDi, H, Barron, A B, Li, S, Honkanen, M, Loukola, O J, Peng, F, Li, W, Marshall, J A R, Cope, A, Vasilaki, E and Solvi, C (2021) ‘Non-numerical strategies used by bees to solve numerical cognition tasks’, Proceedings of the Royal Society Series B (online first).

5. Marshall, J A R (2021) ‘Borrowing bee brains’, New Scientist, 249(3322), p. 23.

2020

1. MaBouDi, H, Marshall, J A R and Barron, A (2020) ‘Honeybees solve a multi-comparison ranking task by probability matching’, Proceedings of the Royal Society Series B (online first).

2019

1. Bose, T, Pirrone, A, Reina, A, Marshall, J A R (2019) ‘Comparison of magnitude-sensitive sequential sampling models in a simulation-based study’, Journal of Mathematical Psychology (online first).

2. Talamali, S, Bose, T, Haire, M, Xu, X, Marshall, JA R and Reina, A (2019) ‘Sophisticated collective foraging with minimalist agents: a swarm robotics test’, Swarm Intelligence (online first).

3. Marshall, J A R, Reina, A, Bose, T (2019) ‘Multiscale Modelling Tool: mathematical modelling of collective behaviour without the maths’, PLoS one, 14(9).

4. Bose, T, Bottom, F, Reina, A, Marshall, J A R (2019) ‘Frequency-sensitivity and magnitude-sensitivity in decision-making: predictions of a theoretical model-based study’, Computational Brain & Behavior (online first).

5. Bose, T, Reina, A, Marshall, J A R (2019) ‘Inhibition and excitation shape activity selection: effect of oscillations in a decision-making circuit’, Neural Computation, 31, pp. 870–896.

6. Marshall, J A R, Kurvers, R, Krause, J and Wolf, M (2019) ‘Quorums enable optimal pooling of independent judgements in biological systems’ eLife 8:e40368.

2018

1. Cope, A, Vasilaki, E, Minors, D, Sabo, C, Marshall, J A R and Barron, A B (2018) ‘Abstract concept learning in a simple neural network inspired by the insect brain’, PLoS Computational Biology, 14(9): e1006435.

2. Reina, A, Bose, T, Trianni, V and Marshall, J A R (2018) ‘Psychophysical laws and the superorganism’, Scientific Reports, 8, 4387.

3. Booton, R, Yamaguchi, R, Marshall, J A R, Childs, D Z and Iwasa, Y (2018) ‘Interactions between immunotoxicants and parasite stress: implications for host health’, Journal of Theoretical Biology, 445, pp. 120–127.

4. Pirrone, A, Azab, H, Hayden, B Y, Stafford, T and Marshall, J A R (2018) ‘Evidence for the speed-value trade-off: human and monkey decision making is magnitude sensitive’, Decision, 5(2), pp. 129–142.

5. Richardson, T O, Mullon, C, Marshall, J A R, Franks, N R and Schlegel, T (2018) ‘The influence of the few: a stable “oligarchy” controls information flow in house-hunting ants’, Proceedings of the Royal Society B, 285.

2017

1. Marshall, J A R, Brown, G and Radford, A N (2017) ‘Individual confidence-weighting and group decision-making’, Trends in Ecology and Evolution, 32(9), pp. 636–645.

2. Pirrone, A, Marshall, J A R and Stafford, T (2017) ‘A drift diffusion model account of the semantic congruity effect’, Journal of Numerical Cognition, 3, pp. 77–96.

3. Quickfall, C G and Marshall, J A R (2017) ‘The evolution of mutualism with modifiers’, Ecology and Evolution, 7, pp. 6114–6118.

4. Ramirez, J C and Marshall, J A R (2017) ‘Can natural selection encode Bayesian priors?’, Journal of Theoretical Biology, 426, pp. 57–66.

5. Reina, A, Trianni, V, Marshall, J A R and Bose, T (2017) ‘A model of the best-of-N nest-site selection process in honeybees’, Physical Review E, 95, 052411.

6. Bose, T, Reina, A, Marshall, J A R (2017) ‘Collective decision-making’, Current Opinion in Behavioral Sciences, 16, pp. 30–34.

7. Booton, R D, Iwasa, Y, Marshall, J A R and Childs, D Z (2017) ‘Stress-mediated Allee effects can cause the sudden collapse of honey bee colonies’, Journal of Theoretical Biology, 420, pp. 213–219.

8. Cope, A J, Sabo, C, Vasilaki, E, Barron, A B and Marshall, J A R (2017) ‘A computational model of the integration of landmarks and motion in the insect central complex’, PLoS one, 12(2): e0172325.

2016

1. Marshall, J A R (2016) ‘What is inclusive fitness theory, and what is it for?’, Current Opinion in Behavioural Sciences, 12, pp. 103–108.

2. Reid, C R, MacDonald, H, Mann, R P, Marshall, J A R, Latty, T and Garnier, S (2016) ‘Decision-making without a brain: how an amoeboid organism solves the two-armed bandit’, Journal of the Royal Society: Interface, 13: 20160030.

3. Cope, A, Sabo, C, Gurney, K, Vasilaki, E and Marshall, J A R (2016) ‘A model for an angular velocity-tuned motion detector accounting for deviations in the corridor-centering response of the bee’, PLoS Computational Biology, 12(5): e1004887.

2015

1. Barron, A, Gurney, K, Meah, L F, Vasilaki, E and Marshall, J A R (2015) ‘Decision-making and action selection in insects: inspiration from vertebrate-based theories’, Frontiers in Behavioural Neuroscience.

2. Marshall, J A R (2015) Social evolution and inclusive fitness theory: an introduction. Princeton University Press. [Order]

   • Queller, D (2015) ‘The theory of inclusive fitness’, Quarterly Review of Biology, 91, pp. 343–347.

   • Ulrich, E (2016) ‘Inclusive fitness 101: math not required’, Trends in Ecology and Evolution, 31, pp. 178–179.

   • Akçay, E (2015) ‘An apology for inclusive fitness theory’, Evolution.

   • Allen, B (2015) ‘Inclusive fitness theory becomes an end in itself’, BioScience, 65, pp. 1103–1104.

     • Marshall, J A R (2016) ‘Errors in Allen’s review of social evolution and inclusive fitness theory: an introduction’, BioScience, 66, p. 185.

     • Allen, B (2016) ‘Statistical inference is not needed when the solution Is already known’, BioScience, 66, p. 186.

3. Fawcett, T W, Marshall, J A R and Higginson, A D (2015) ‘The evolution of mechanisms underlying behaviour’, Current Zoology, 61, pp. 221–225.

4. Marshall, J A R, Favreau-Peigné, A, Fromhage, L, McNamara, J M, Meah, L F S and Houston, A I (2015) ‘Cross inhibition improves activity selection when switching incurs time costs’, Current Zoology, 61, pp. 242–250.

5. Ramírez, J C and Marshall, J A R (2015) ‘Self-deception can evolve under appropriate costs’, Current Zoology, 61, pp. 382–396.

6. Marshall, J A R (2015) ‘Desperately seeking meaning (review of E O Wilson’s meaning of human existence)’, BioScience, 65, pp. 328–329.

7. Osinga, H M and Marshall, J A R (2015) ‘Adaptive topographies and equilibrium selection in an evolutionary game’, PLoS one, 10(2): e0116307.

2014

1. Birch, J and Marshall, J A R (2014) ‘Queller’s separation condition explained and defended’, American Naturalist, 184, pp. 531–540.

2. Marshall, J A R (2014) ‘Generalisations of Hamilton’s rule applied to non-additive public goods games with random group size’, Frontiers in Ecology and Evolution, 2, p. 40.

3. Pirrone, A, Stafford, T and Marshall, J A R (2014) ‘When natural selection should optimise speed-accuracy trade-offs’, Frontiers in Neuroscience, 8, p. 73.

2013

1. Cassey, T C, Evens, D R, Bogacz, R, Marshall, J A R and Ludwig, C J H (2013) ‘Adaptive sampling of information in perceptual decision-making’, PLoS one, 8(11): e78993.

2. Pais, D, Hogan, P M, Schlegel, T, Franks, N R, Leonard, N E and Marshall, J A R (2013) ‘A mechanism for value-sensitive decision-making’, PLoS one, 8(9): e73216.

3. Marshall, J A R, Trimmer, P C, Houston, A I and McNamara, J M (2013) ‘On evolutionary explanations of cognitive biases’, Trends in Ecology and Evolution, 28, pp. 469–473.

4. Marshall, J A R, Trimmer, P C and Houston, A I (2013) ‘Unbiased individuals use valuable information when making decisions’, Trends in Ecology and Evolution, 28, pp. 444–445.

5. Franks, N R, Richardson, T O, Stroeymeyt, N, Kirby, R W, Amos, W M D, Hogan, P M, Marshall, J A R and Schlegel, T (2013) ‘Speed-cohesion trade-offs in collective decision making in ants and the concept of precision in animal behaviour’, Animal Behaviour, 85, pp. 1233–1244.

6. Zenil, H and Marshall, J A R (2012) ‘Computational aspects of essential properties of evolution and life’, ACM Ubiquity, 2013, pp. 1–16.

7. Trimmer, P C, Marshall, J A R, Fromhage, L, McNamara, J M and Houston, A I (2012) ‘Understanding the placebo effect from an evolutionary perspective’, Evolution and Human Behavior, 34, pp. 8–15.

2012

1. Zenil, H, Gershenon, C, Marshall, J A R and Rosenblueth, D A (2012) ‘Life as thermodynamic evidence of algorithmic structure in natural environments’, Entropy, 14, pp. 2173–2191.

2. Marshall, J A R, Bogacz, R and Gilchrist, I D (2012) ‘Consistent implementation of decisions in the brain’, PLoS one, 7(9): e43443.

3. Marshall, J A R and Neumann, F (2012) ‘Foundations of search – a perspective from computer science’, in Todd, Hills and Robbins (eds.) Cognitive search: evolution, algorithms and the brain. MIT Press.

4. Schooler, L et al. (2012) ‘Search environments, representation, and encoding’, in Todd, Hills and Robbins (eds.) Cognitive search: evolution, algorithms and the brain. MIT Press.

5. Trimmer, P C, McNamara, J M, Houston, A I and Marshall, J A R (2012) ‘Does natural selection favour the Rescorla-Wagner rule?’, Journal of Theoretical Biology, 302, pp. 39–52.

6. Franklin, E, Robinson, E J H, Marshall, J A R, Sendova-Franks, A and Franks, N R (2012) ‘Do ants need to be old and experienced to teach?’, Journal of Experimental Biology, 215, pp. 1287–1292.

7. Seeley, T D, Visscher, P K, Schlegel, T, Hogan, P M, Franks, N R and Marshall, J A R (2012) ‘Stop signals provide cross inhibition in collective decision-making by honeybee swarms’, Science, 335, pp. 108–111.

   • Perspective by Jeremy Niven

   • Faculty of 1000 citation by Martin Giurfa

2011

1. Houston, A I, Trimmer, P C, Fawcett, T W, Higginson, A D, Marshall, J A R and McNamara, J M (2011) ‘Is optimism optimal? Functional causes of apparent behavioural biases’, Behavioral Processes, 89, pp. 172–178.

2. Marshall, J A R (2011) ‘Group selection and kin selection: formally equivalent approaches’, Trends in Ecology and Evolution, 26, pp. 325–332.

3. Robinson, E J H, Franks, N R, Ellis, S, Okuda, S and Marshall, J A R (2011) ‘A simple threshold rule is sufficient to explain sophisticated collective decision-making’, PLoS one, 6(5): e19981.

4. Abott, P et al. (2011) ‘Inclusive fitness theory and eusociality’, Nature, 471, E1–E4.

5. Trimmer, P C, Houston, A I, Marshall, J A R, Mendl, M T, Paul, E S and McNamara, J M (2011) ‘Decision-making under uncertainty: biases and Bayesians’, Animal Cognition, 14, pp. 465–476.

6. Marshall, J A R (2011) ‘Optimal voting in groups with convergent interests’, AAAI Spring Symposium Series.

7. Stroeymeyt, N, Robinson, E J H, Hogan, P M, Marshall, J A R, Giurfa, M and Franks, N R (2011) ‘Experience-dependent flexibility in collective decision-making by house-hunting ants’, Behavioral Ecology, 22, pp. 535–542.

8. Marshall, J A R, Bogacz, R, Planqué, R, Kovacs, T and Franks, N R (2011) ‘On optimal decision-making in brains and social insect colonies’, in Seth et al. (eds.) Modelling natural action selection. Cambridge University Press.

2010

1. Trianni, V, Tuci, L, Passino, K M and Marshall, J A R (2010) ‘Swarm cognition: an interdisciplinary approach to the study of self-organising biological collectives’, Swarm Intelligence, 5, pp. 3–18.

2. Marshall, J A R, McNamara, J M and Houston, A I (2010) ‘The state of Darwinian theory’, Behavioral Ecology and Sociobiology, 65, pp. 417–420.

3. Marshall, J A R (2010) ‘Ultimate causes and the evolution of altruism’, Behavioral Ecology and Sociobiology, 65, pp. 503–512.

4. McNamara, J M, Trimmer, P C, Eriksson, A, Marshall, J A R and Houston, A I (2010) ‘Environmental variability can select for optimism or pessimism’, Ecology Letters, 14, pp. 58–62.

5. Marshall, J A R (2010) ‘Queller’s rule OK: comment on van Veelen “when inclusive fitness is right and when it can be wrong”’, Journal of Theoretical Biology, 270, pp. 185–188.

2009

1. Marshall, J A R (2009) ‘The donation game with roles played between relatives’, Journal of Theoretical Biology, 260, pp. 386–391.

2. Marshall, J A R and Franks, N R (2009) ‘Colony-level cognition’, Current Biology, 19, R395–R396.

3. Marshall, J A R, Bogacz, R, Dornhaus, A, Planqué, R, Kovacs, T and Franks, N R (2009) ‘On optimal decision making in brains and social insect colonies’, Journal of the Royal Society: Interface, 6, pp. 1065–1074.

4. Franks, N R, Dornhaus, A, Marshall, J A R and Dechaume-Moncharmont, F X (2009) ‘The dawn of a golden age in mathematical insect sociobiology’, in Gadau and Fewell (eds.) Organization of insect societies. Harvard University Press.

2008

1. Trimmer, P, Bogacz, R, Houston, A I, Marshall, J A R, McNamara, J M, Mendl, M and Paul, E (2008) ‘Mammalian choices: combining fast-but-inaccurate and slow-but-accurate decision-making systems’, Proceedings of the Royal Society B, 275, pp. 2353–2361.

2007

1. Franks, N R, Hooper, J W, Gumn, M, Bridger, T H, Marshall, J A R, Gross, R and Dornhaus, A (2007) ‘Moving targets: collective decisions and flexible choices in house-hunting ants’, Swarm Intelligence, 2, pp. 81–94.

2. Planqué, R, Dechaume-Moncharmont, F X, Franks, N R, Kovacs, T and Marshall, J A R (2007) ‘Why do house-hunting ants recruit in both directions?’, Naturwissenschaften, 94, pp. 1028–1042.

3. Planqué, R, Dornhaus, A, Franks, N R, Kovacs, T and Marshall, J A R (2007) ‘Weighting waiting in collective decision-making’, Behavioral Ecology and Sociobiology, 61, pp. 347–356.

4. Marshall, J A R and Franks, N R (2007) ‘Computer modelling in behavioral and evolutionary ecology: whys and wherefores’, in Laubichler and Müller (eds.) Modelling biology – structures, behaviors, evolution. Vienna Series in Theoretical Biology, MIT Press.

2006

1. Marshall, J A R, Dornhaus, A, Franks, N R and Kovacs, T (2006) ‘Noise, cost and speed-accuracy trade-offs: decision-making in a decentralized system’, Journal of the Royal Society: Interface, 3, pp. 243–254.

2004

1. Marshall, J A R (2004) ‘Review of “The structure of evolutionary theory” by S J Gould’, Artificial Life, 10, pp. 113–115.

2003

1. Marshall, J A R and Rowe, J E (2003) ‘Viscous populations and their support for reciprocal cooperation’, Artificial Life, 9, pp. 327–334.

2. Marshall, J A R and Rowe, J E (2003) ‘Kin selection may inhibit the evolution of reciprocation’, Journal of Theoretical Biology, 222, pp. 331–335.