https://research-explorer.ista.ac.at 2000-01-01T00:00+00:00 1 monthly https://research-explorer.ista.ac.at/record/18895 Cadei, Riccardo Locatello, Francesco ; https://orcid.org/0000-0002-4850-0683 Cremer, Sylvia M ; https://orcid.org/0000-0002-2193-3868 Lindorfer, Lukas Schmid, Cordelia 2024 ISTAnt is a new ecological dataset for social immunity and represents the first real-world benchmark for causal inference downstream tasks on high-dimensional observations. It analyzes grooming behavior in the ant Lasius neglectus in groups of three worker ants. The workers for the experiment were obtained from their laboratory stock colony, which had been collected from the field in 2022 in the Botanical Garden Jena, Germany. Ant collection and all experimental work were performed in compliance with international, national and institutional regulations and ethical guidelines. For the experiment, the body surface of one of the three ants was treated with a suspension of either of two microparticle types (diameter ~5 µm) to induce grooming by the two nestmates, which were individually color-coded by application of a dot of blue or orange paint, respectively. The three ants were housed in small plastic containers (diameter 28mm, height 30mm) with moistened, plastered ground and the interior walls covered with PTFE (polytetrafluoroethane) to hamper climbing by the ants. Filming occurred in a temperature- and humidity-controlled room at 23°C within a custom-made filming box with controlled lighting and ventilation conditions. We set up nine ant groups at a time (always containing both treatments) and placed them randomly on positions 1-9 marked on the floor in a 3x3 grid, about 3mm from each other. The experiment was performed on two consecutive days. Videos were acquired using a USB camera (FLIR blackfly S BFS-U3-120S4C, Teledyne FLIR) with a high-performance lens (HP Series 25mm Focal Length, Edmund optics 86-572) in OBS studio 29.0.0 \citep{bailey2017obs} at a framerate of 30 FPS and a resolution of 2500x2500 pixels. From each original video (105x105 mm), we generated nine individual videos .mkv (each ~32x32 mm, 770x770 pixels) by determining exact coordinates per container from one frame in GIMP 2.10.36 and cropping of the videos with FFmpeg 6.1.1. Annotation was performed over two consecutive days by three observers who had not been involved in the experimental setup or recording and were unaware of the treatment assignments to ensure bias-free behavioral annotation. They annotated the behavior of the ants during video observations, using custom-made software that saves the start and end frames of behaviors marked in a .csv file (see 'annotations' folder). In one of the videos, one of the nestmates' legs got inadvertently stuck to its body surface during the color-coding, interfering with its behavior, so the video was discarded. This left 44 videos from 5 independent setups (n=24 of treatment 1 and n=20 of treatment 2) of 10 minutes each for a total of 792 000 annotated frames (see 'video' folder). For each video, we provide the following information: the number of the set to which it belongs (1-5); the number of the position within the set reflecting the position of the ant group under the camera (1-9), for which we also provide ‘coordinates’ in the 3x3 grid (taking values -1/0/1 for both X and Y axis); treatment (1 or 2); the hour of the day when the recording was started (in 24h CEST); experimental day (A or B); the top left coordinate of the cropping square from the original video (CropX/CropY); the person annotating the video (given as A, B, C); the date of annotation (1: first day, 2: second day) and in which order the videos were annotated by each person, both reflecting a possible training effect of the person (see 'experiments_settings.csv' file). https://research-explorer.ista.ac.at/record/18895 Institute of Science and Technology Austria info:eu-repo/semantics/altIdentifier/doi/10.6084/M9.FIGSHARE.26484934.V2 info:eu-repo/semantics/openAccess Cadei R, Locatello F, Cremer S, Lindorfer L, Schmid C. ISTAnt. 2024. doi:<a href="https://doi.org/10.6084/M9.FIGSHARE.26484934.V2">10.6084/M9.FIGSHARE.26484934.V2</a> ddc:570 ISTAnt info:eu-repo/semantics/other doc-type:other research_data_reference http://purl.org/coar/resource_type/c_ddb1 https://research-explorer.ista.ac.at/record/19903 Hübner, Valentin ; https://orcid.org/0009-0001-5009-4987 2025 Cooperation, that is, one person paying a cost for another's benefit, is a fundamental principle without which no form of society could exist. The extent to which humans cooperate with each other is also an essential feature that differentiates them from other animals. Cooperation occurs even in the absence of altruistic motivations, when it is selfishly incentivised by the expectation of a future reward. For example, many economic interactions are well described that way. This kind of cooperation requires that people exhibit reciprocal behaviour that acts as a mechanism that rewards cooperation. With game-theoretic models, it is possible to formally study potential such mechanisms and under what conditions they can exist. This thesis contributes to this effort by analysing recently introduced models of cooperation that advance on previous work by taking into account the potential for pre-existing inequality among cooperating individuals as well as the different forms that reciprocity can take. Individuals may differ both intrinsically, in their abilities, as well as extrinsically, in the amount of resources they have available. Allowing for such differences in a model of cooperation helps to understand how inequality affects the potential for, and outcomes of, cooperation among unequals. In this thesis, it is shown that in the presence of intrinsic inequality, a similar unequal distribution of resources can increase the potential for cooperation. This effect is stronger the smaller the group is in which cooperation takes place. It is also shown that under particular assumptions, if the unequal members of a group vary the size of their contributions to a cooperative effort over time, they can thereby increase their efficiency and improve the collective outcome. Cooperative behaviour in a two-person interaction can be rewarded either by direct reciprocation whenever the same two people interact again, or indirectly by a third party who observed the interaction. In the latter case of indirect reciprocity, individuals are proximally rewarded by a good reputation, which ultimately translates to being rewarded with cooperative behaviour by others. This mechanism can enable selfishly motivated cooperation even in circumstances where individuals are unlikely to meet again, akin to how money facilitates trade. While these two forms of reciprocity have mostly been studied in isolation, this thesis analyses both direct and indirect reciprocity in a general model in order to compare their relative effectiveness under different circumstances. The contribution of this thesis is an extension of previous work regarding a specific kind of interaction, whose parameters allow for convenient mathematical analysis, to the most general set of possible interactions. https://research-explorer.ista.ac.at/record/19903 https://research-explorer.ista.ac.at/download/19903/19976 eng Institute of Science and Technology Austria info:eu-repo/semantics/altIdentifier/doi/10.15479/AT-ISTA-19903 info:eu-repo/semantics/altIdentifier/issn/2663-337X https://creativecommons.org/licenses/by-nc/4.0/ info:eu-repo/semantics/openAccess Hübner V. Reciprocity and inequality in social dilemmas. 2025. doi:<a href="https://doi.org/10.15479/AT-ISTA-19903">10.15479/AT-ISTA-19903</a> ddc:519 Reciprocity and inequality in social dilemmas ISTA Thesis info:eu-repo/semantics/doctoralThesis doc-type:DoctoralThesis DoctoralThesis http://purl.org/coar/resource_type/c_db06 https://research-explorer.ista.ac.at/record/9402 Schmid, Laura ; https://orcid.org/0000-0002-6978-7329 Chatterjee, Krishnendu ; https://orcid.org/0000-0002-4561-241X Hilbe, Christian ; https://orcid.org/0000-0001-5116-955X Nowak, Martin A. 2021 Direct and indirect reciprocity are key mechanisms for the evolution of cooperation. Direct reciprocity means that individuals use their own experience to decide whether to cooperate with another person. Indirect reciprocity means that they also consider the experiences of others. Although these two mechanisms are intertwined, they are typically studied in isolation. Here, we introduce a mathematical framework that allows us to explore both kinds of reciprocity simultaneously. We show that the well-known ‘generous tit-for-tat’ strategy of direct reciprocity has a natural analogue in indirect reciprocity, which we call ‘generous scoring’. Using an equilibrium analysis, we characterize under which conditions either of the two strategies can maintain cooperation. With simulations, we additionally explore which kind of reciprocity evolves when members of a population engage in social learning to adapt to their environment. Our results draw unexpected connections between direct and indirect reciprocity while highlighting important differences regarding their evolvability. https://research-explorer.ista.ac.at/record/9402 https://research-explorer.ista.ac.at/download/9402/14496 eng Springer Nature info:eu-repo/semantics/altIdentifier/doi/10.1038/s41562-021-01114-8 info:eu-repo/semantics/altIdentifier/e-issn/2397-3374 info:eu-repo/semantics/altIdentifier/wos/000650304000002 info:eu-repo/semantics/altIdentifier/pmid/33986519 info:eu-repo/semantics/openAccess Schmid L, Chatterjee K, Hilbe C, Nowak MA. A unified framework of direct and indirect reciprocity. <i>Nature Human Behaviour</i>. 2021;5(10):1292–1302. doi:<a href="https://doi.org/10.1038/s41562-021-01114-8">10.1038/s41562-021-01114-8</a> ddc:000 A unified framework of direct and indirect reciprocity info:eu-repo/semantics/article doc-type:Article Article http://purl.org/coar/resource_type/c_2df8fbb1 https://research-explorer.ista.ac.at/record/17329 Alistarh, Dan-Adrian ; https://orcid.org/0000-0003-3650-940X Chatterjee, Krishnendu ; https://orcid.org/0000-0002-4561-241X Karrabi, Mehrdad ; https://orcid.org/0009-0007-5253-9170 Lazarsfeld, John M 2024 We initiate the study of game dynamics in the population protocol model: n agents each maintain a current local strategy and interact in pairs uniformly at random. Upon each interaction, the agents play a two-person game and receive a payoff from an underlying utility function, and they can subsequently update their strategies according to a fixed local algorithm. In this setting, we ask how the distribution over agent strategies evolves over a sequence of interactions, and we introduce a new distributional equilibrium concept to quantify the quality of such distributions. As an initial example, we study a class of repeated prisoner's dilemma games, and we consider a family of simple local update algorithms that yield non-trivial dynamics over the distribution of agent strategies. We show that these dynamics are related to a new class of high-dimensional Ehrenfest random walks, and we derive exact characterizations of their stationary distributions, bounds on their mixing times, and prove their convergence to approximate distributional equilibria. Our results highlight trade-offs between the local state space of each agent, and the convergence rate and approximation factor of the underlying dynamics. Our approach opens the door towards the further characterization of equilibrium computation for other classes of games and dynamics in the population setting. https://research-explorer.ista.ac.at/record/17329 https://research-explorer.ista.ac.at/download/17329/17335 eng Association for Computing Machinery info:eu-repo/semantics/altIdentifier/doi/10.1145/3662158.3662768 info:eu-repo/semantics/altIdentifier/isbn/9798400706684 info:eu-repo/semantics/openAccess Alistarh D-A, Chatterjee K, Karrabi M, Lazarsfeld JM. Game dynamics and equilibrium computation in the population protocol model. In: <i>Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing</i>. Association for Computing Machinery; 2024:40-49. doi:<a href="https://doi.org/10.1145/3662158.3662768">10.1145/3662158.3662768</a> ddc:000 Game dynamics and equilibrium computation in the population protocol model info:eu-repo/semantics/conferenceObject doc-type:ConferenceObject ConferenceObject http://purl.org/coar/resource_type/c_5794