Overall, the project has proceeded even better than expected. Indeed, significant achievements were accomplished in all tasks, yielding publications in prestigious venues in both computer science and biology, including:
[1] "Intermittent inverse-square Lévy walks are optimal for finding targets of all sizes", Science Advances 2021. This paper theoretically studies the computational benefits of utilizing a Levy flight pattern while searching for targets.
[2] "A locally-blazed ant trail achieves efficient collective navigation despite limited information", eLife 2016. The paper combines extensive experiments in P. longicornis ants and theoretical investigations. It demonstrated the role played by noise in the navigation process of ants. The paper has received media coverage, with articles centered around it appearing in "Le Monde" and "Haaretz" daily newspapers.
[3] "Navigating in trees with permanently noisy advice", TALG 2021. The paper investigates the model in [2], focusing on tree structures, and exhibiting several phase transition phenomena.
[4] “Ant collective cognition allows for efficient navigation through disordered environments.” eLife, 2020. The paper studies collaborative transport by P. longicornis ants, combining extensive experiments with theoretical investigations. It shows that in highly unreliable environments, these ants use their numbers to collectively extend their sensing range, and thus shorten their traversal times.
[5] "Breathe before speaking: efficient information dissemination despite noisy, limited and anonymous communication", Distributed Computing, 2017. The paper introduces the computational study of communication noise in the context of stochastically interacting agents.
[6] "Limits on reliable information flows through stochastic populations", PLoS Comp. Biology 14(6), 2018. (Extended abstract in ITCS 2018.) This paper indicates that when there is no structure, the communication is random, and when all facets of the communication are noisy, basic distributed computations cannot be completed efficiently. We further demonstrated this fundamental lower bound through an experiment in Cataglyphis niger ants.
[7] "Reinforcement learning enables resource-partitioning in foraging bats", Current Biology, 2020. The paper provides insights into the mechanisms allowing lesser longnosed bats to exploit replenishing resources while being in competition. The paper combines extensive experiments in bats with theoretical investigations. An article centered around this paper appeared in the daily Israeli newspaper Ynet.
[8] "Multi-round cooperative search games with multiple players. JCSS 2020. (Extended abstract in ICALP 2019). This paper investigates a simplified version of the setting in [7], from a mechanism design perspective.
[9] "Parallel Bayesian Search with No Coordination", J. ACM 2019. (Extended abstract in STOC 2016.) This paper studies distributed search by multiple agents. It highlights the significance of non-coordinating algorithms for being both highly efficient and robust to failures.
[10] "The ANTS Problem", Distributed Computing 2017. This paper establishes a basic framework for relating information parameters and time efficiency parameters with respect to central search foraging.
