Periodic Reporting for period 4 - ANTSolve (A multi-scale perspective into collective problem solving in ants)
Periodo di rendicontazione: 2022-12-01 al 2024-05-31
Ants coordinate their action in a distributed way without strong hierarchies or centralized decision-makers. In today’s world, society is heading in similar directions: the internet, social media, and even electric networks are becoming increasingly decentralized. However, as recent history teaches us, functioning in a collectively advantageous manner within this setting is far from trivial. It is, therefore, highly interesting and relevant to study how the ants who have 150 million years of experience on these issues cooperate to collectively face large-scale problems.
Our objective is to formulate a multi-scale description of problem-solving by Paratrechina longicornis crazy ants. The problems we confront the ants with are natural – cooperatively transporting large objects to their nest. We challenge the ants with various obstacles and confinements and measure how they react to them as individuals and as groups. We then link these reactions to the concept of problem-solving, wherein one can define group success rates and efficiency. Further, by duplicating some of the ant mazes on a much larger scale we compared the problem solving capabilities of ants groups to those of human groups. Using these comparisons, we can understand the differences between the social structures of these two species and how they facilitate coordination and collective cognition. Finally, inspired by these results, we will use modeling and theory to broaden our definitions and understandings of the concept of collective cognition.
Our objective is to formulate a multi-scale description of problem-solving by Paratrechina longicornis crazy ants. The problems we confront the ants with are natural – cooperatively transporting large objects to their nest. We challenge the ants with various obstacles and confinements and measure how they react to them as individuals and as groups. We then link these reactions to the concept of problem-solving, wherein one can define group success rates and efficiency. Further, by duplicating some of the ant mazes on a much larger scale we compared the problem solving capabilities of ants groups to those of human groups. Using these comparisons, we can understand the differences between the social structures of these two species and how they facilitate coordination and collective cognition. Finally, inspired by these results, we will use modeling and theory to broaden our definitions and understandings of the concept of collective cognition.
It is well known that group living holds many advantages, but is collective intelligence one of these? Is a group more intelligent than its smartest individual? This question is not well-defined and, thus, difficult to address. In this project, we approached these questions by studying collective problem-solving by groups of ants.
We studied these questions by considering longhorn crazy ant cooperative transport a behavior in which many ants cooperate to carry a large item of food as a group. This behavior provides a good route for studying collective cognition since, in a natural setting, to get the load to their nest the ants must overcome a large number of highly variable open-ended environmental challenges. An important part of our project was to challenge ant groups with numerous puzzles inspired by different environmental challenges. These allowed us to compare between the performances of different group size (in some cases, down to a single individual) as well as try to decipher the ways in which ants coordinate to overcome these challenges. The main puzzles we studied were a binary decision between two alternative routes; the ant-in-a-labyrinth puzzle: navigation through highly disordered environments; pebble clearing, cooperative transport that requires preparatory modification of the environment, and the piano movers’ puzzle where an odd-shaped “piano” must be maneuvered within a tight environment. To summarize our findings in the briefest manner, ants display collective cognitive skills that make them very general problem-solvers. Importantly, these collective emergent problem-solving capabilities do not erase individual cognition but rather use it and feed back into it to maximally increase performance.
These observations led to and were backed by experiments that were specifically designed to understand how ants achieve increased capabilities. Our experiments strengthened our initial assumptions on the ways ants coordinate their pulling efforts demonstrating that most of the required communication comes from the pulling itself. We further find, that ants actively react to the progress of the load, for example, decreasing their energy use when things are running smoothly. On the group level, we combined a model of individual ants with a physics-engine typically used to simulate motions in computer games. This allowed us to prove that communication by forces is the main source of coordination between ants and understand how the group reacts to constraints. We also constructed a robot that mimics an individual ant and tests her effect on the group. This led to the first experimental evidence ever of the common hypothesis that at criticality, the responsiveness of animal groups to external perturbations is maximized.
Another rare species that performs cooperative transport is our species. We challenged people with the exact same pian-movers-problem that was given to ants. Here again, the puzzle was presented to both individuals and groups of various sizes. We found that, when people are not allowed to communicate freely, group performance deteriorates below that of the average individual person. This happens because, in large groups, people forsake their individual understanding and opinions in favor of achieving consensus. If allowed to speak a group can save its performance to match (but never exceed) that of an individual.
On the theoretical front we have studied ways to measure information flows and the degree of synergy within large coordinated groups. We have developed tools for studying information loops within communication networks and set a much sought after, theoretical basis for the statement that “the whole is larger than the sum of its parts”.
Our results were published in high-end journals and many others are currently under review. Our work has been disseminated in a large number of talks, mainly in Europe and the United States, by the PI and other project members. Our human cooperation experiments were accompanied by a large outreach project in which thousands of participants were exposed firsthand to ant cooperation and collective cognition. Further on the outreach front, some of the ideas inspired by this project ended up in an educational scientific comic book that includes fifty activities with live ants that just about anyone can do and try to understand.
We studied these questions by considering longhorn crazy ant cooperative transport a behavior in which many ants cooperate to carry a large item of food as a group. This behavior provides a good route for studying collective cognition since, in a natural setting, to get the load to their nest the ants must overcome a large number of highly variable open-ended environmental challenges. An important part of our project was to challenge ant groups with numerous puzzles inspired by different environmental challenges. These allowed us to compare between the performances of different group size (in some cases, down to a single individual) as well as try to decipher the ways in which ants coordinate to overcome these challenges. The main puzzles we studied were a binary decision between two alternative routes; the ant-in-a-labyrinth puzzle: navigation through highly disordered environments; pebble clearing, cooperative transport that requires preparatory modification of the environment, and the piano movers’ puzzle where an odd-shaped “piano” must be maneuvered within a tight environment. To summarize our findings in the briefest manner, ants display collective cognitive skills that make them very general problem-solvers. Importantly, these collective emergent problem-solving capabilities do not erase individual cognition but rather use it and feed back into it to maximally increase performance.
These observations led to and were backed by experiments that were specifically designed to understand how ants achieve increased capabilities. Our experiments strengthened our initial assumptions on the ways ants coordinate their pulling efforts demonstrating that most of the required communication comes from the pulling itself. We further find, that ants actively react to the progress of the load, for example, decreasing their energy use when things are running smoothly. On the group level, we combined a model of individual ants with a physics-engine typically used to simulate motions in computer games. This allowed us to prove that communication by forces is the main source of coordination between ants and understand how the group reacts to constraints. We also constructed a robot that mimics an individual ant and tests her effect on the group. This led to the first experimental evidence ever of the common hypothesis that at criticality, the responsiveness of animal groups to external perturbations is maximized.
Another rare species that performs cooperative transport is our species. We challenged people with the exact same pian-movers-problem that was given to ants. Here again, the puzzle was presented to both individuals and groups of various sizes. We found that, when people are not allowed to communicate freely, group performance deteriorates below that of the average individual person. This happens because, in large groups, people forsake their individual understanding and opinions in favor of achieving consensus. If allowed to speak a group can save its performance to match (but never exceed) that of an individual.
On the theoretical front we have studied ways to measure information flows and the degree of synergy within large coordinated groups. We have developed tools for studying information loops within communication networks and set a much sought after, theoretical basis for the statement that “the whole is larger than the sum of its parts”.
Our results were published in high-end journals and many others are currently under review. Our work has been disseminated in a large number of talks, mainly in Europe and the United States, by the PI and other project members. Our human cooperation experiments were accompanied by a large outreach project in which thousands of participants were exposed firsthand to ant cooperation and collective cognition. Further on the outreach front, some of the ideas inspired by this project ended up in an educational scientific comic book that includes fifty activities with live ants that just about anyone can do and try to understand.
Progress beyond state of the art was achieved on several fronts:
•We have constructed a customized load that allows for the measurement of single ant forces down to the milli-Newton scale.
•We have constructed an ant robot for precise mechanical interactions with the carrying ants.
•We have used this robot to provide the first experimental evidence in any animal group of the important assumption that there is an increase in susceptibility at the critical state.
•We have discovered a new biological phenomenon wherein the ants clear debris from the anticipated future path of the moving object.
•We have constructed a new setup that allows us to challenge and groups of different sizes (down to a single individual) with the same precise puzzle. This was never done before.
•We have confronted human groups of different sizes with the same puzzle.
•We were able to conduct meaningful comparisons between collective problem-solving in ants and humans.
•We performed modeling, which includes both agent-based modules and physics engine modules, which provided us with a multi-scale, environment-sensitive, general-purpose description of a collective animal group behavior.
•We tracked ant groups of different sizes as they confronted binary decisions. We show a dynamic decision-making process and use it to expand current models for decision-making suggested in the field of neuroscience.
•For the first time, we show how real ants tackle the famous ant-in-a-labyrinth problem. We demonstrate how the ants surpass known physics-inspired solutions to this problem.
•We have constructed a customized load that allows for the measurement of single ant forces down to the milli-Newton scale.
•We have constructed an ant robot for precise mechanical interactions with the carrying ants.
•We have used this robot to provide the first experimental evidence in any animal group of the important assumption that there is an increase in susceptibility at the critical state.
•We have discovered a new biological phenomenon wherein the ants clear debris from the anticipated future path of the moving object.
•We have constructed a new setup that allows us to challenge and groups of different sizes (down to a single individual) with the same precise puzzle. This was never done before.
•We have confronted human groups of different sizes with the same puzzle.
•We were able to conduct meaningful comparisons between collective problem-solving in ants and humans.
•We performed modeling, which includes both agent-based modules and physics engine modules, which provided us with a multi-scale, environment-sensitive, general-purpose description of a collective animal group behavior.
•We tracked ant groups of different sizes as they confronted binary decisions. We show a dynamic decision-making process and use it to expand current models for decision-making suggested in the field of neuroscience.
•For the first time, we show how real ants tackle the famous ant-in-a-labyrinth problem. We demonstrate how the ants surpass known physics-inspired solutions to this problem.