Biology subjects

Bredeche, N.

Publications and source records attributed to Bredeche, N..

3 recordsLinked to original sources

bioRxiv2020

Nothing better to do? Environment quality and the evolution of cooperation by partner choice

The effects of partner choice have been documented in a large number of biological systems such as sexual markets, interspecific mutualisms, or human cooperation. There are, however, a number of situations in which one would expect this mechanism to play a role, but where no such effect has ever been demonstrated. This is the case in particular in many intraspecific interactions, such as collective hunts, in non-human animals. Here we use individual-based simulations to solve this apparent paradox. We show that the conditions for partner choice to operate are in fact restrictive. They entail that individuals can compare social opportunities and choose the best. The challenge is that social opportunities are often rare because they necessitate the co-occurrence of (i) at least one available partner, and (ii) a resource to exploit together with this partner. This has three consequences. First, partner choice cannot lead to the evolution of cooperation when resources are scarce, which explains that this mechanism could never be observed in many cases of intraspecific cooperation in animals. Second, partner choice can operate when partners constitute in themselves a resource, which is the case in sexual interactions and interspecific mutualisms. Third, partner choice can lead to the evolution of cooperation when individuals live in a rich environment, and/or when they are highly efficient at extracting resources from their environment.

evolutionary biology↗

bioRxiv2019

Using MAP-Elites to Optimize Self-Assembling Behaviors in a Swarm of Bio-micro-robots

We are interested in programming a swarm of molecular robots that can perform self-assembly to form specific shapes at a specific location. Programming such robot swarms is challenging for two reasons. First, the goal is to optimize both the parameters and the structure of chemical reaction networks. Second, the search space is both high-dimensional and deceptive. In this paper, we show that MAP-Elites, an algorithm that searches for both high-performing and diverse solutions, outperforms previous state-of-the-art optimization methods.

bioengineering↗

bioRxiv2018

Individual selection leads to collective efficiency through coordination

Evolutionary game theory shows that social interactions involving coordination between individuals are subject to an \"evolutionary trap.\" Once a suboptimal strategy has evolved, mutants playing an alternative strategy are counterselected because they fail to coordinate with the majority. This creates a detrimental situation from which evolution cannot escape. To determine how this problem materializes in a model with a greater degree of realism than conventional game-theoretical models, we simulate the life and the long-term evolution of a population of individuals playing a two-player coordination game, using the framework of evolutionary robotics. We first confirm the existence of an evolutionary trap in a simple setting. We then, however, reveal that this problem disappears in a more realistic setting where individuals need to coordinate with one another. In this setting, robots evolve an ability to adapt plastically their behavior to one another, as this improves the efficiency of their interaction. This ability has an unintended evolutionary consequence: a genetic mutation affecting one individuals behavior also indirectly alters their partners behavior because the two individuals influence one another, which is called an \"indirect genetic effect\". Consequently, pairs of partners can virtually change strategy together with a single mutation, and the evolutionary barrier between alternative strategies disappears. This finding reveals a general principle that could play a role in nature to smoothen the transition to efficient collective behaviors in all games with multiple equilibriums.

evolutionary biology↗